U.S. patent application number 14/014120 was filed with the patent office on 2015-02-05 for predictive mobility in cellular networks.
This patent application is currently assigned to QUALCOMM Incorporated. The applicant listed for this patent is QUALCOMM Incorporated. Invention is credited to Olufunmilola O. Awoniyi-Oteri, Robert Sean Daley, Thomas E. Kilpatrick, II, Roy Franklin Quick, JR..
Application Number | 20150038140 14/014120 |
Document ID | / |
Family ID | 52427609 |
Filed Date | 2015-02-05 |
United States Patent
Application |
20150038140 |
Kind Code |
A1 |
Kilpatrick, II; Thomas E. ;
et al. |
February 5, 2015 |
PREDICTIVE MOBILITY IN CELLULAR NETWORKS
Abstract
Methods, systems, and devices are described for managing
wireless communications. In the methods, systems, and devices, a
subset of a set of neighboring cells is identified for measurement
by a mobile device. The subset of neighboring cells is identified
based on historical information associated with mobility patterns
of the mobile device.
Inventors: |
Kilpatrick, II; Thomas E.;
(San Diego, CA) ; Awoniyi-Oteri; Olufunmilola O.;
(San Diego, CA) ; Quick, JR.; Roy Franklin; (San
Diego, CA) ; Daley; Robert Sean; (Del Mar,
CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
QUALCOMM Incorporated |
San Diego |
CA |
US |
|
|
Assignee: |
QUALCOMM Incorporated
San Diego
CA
|
Family ID: |
52427609 |
Appl. No.: |
14/014120 |
Filed: |
August 29, 2013 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61860789 |
Jul 31, 2013 |
|
|
|
Current U.S.
Class: |
455/436 |
Current CPC
Class: |
H04W 8/08 20130101; H04W
36/0055 20130101; H04W 52/362 20130101; H04W 52/325 20130101; H04W
72/0473 20130101; H04W 52/223 20130101; H04W 52/285 20130101; H04W
64/00 20130101; H04W 36/32 20130101; H04W 60/00 20130101; H04W
52/22 20130101; H04W 72/048 20130101; H04W 74/0833 20130101; H04W
64/006 20130101; H04W 72/02 20130101; H04W 52/50 20130101; H04W
68/02 20130101; H04W 36/245 20130101; H04W 36/10 20130101; H04W
52/228 20130101; H04W 36/04 20130101 |
Class at
Publication: |
455/436 |
International
Class: |
H04W 36/32 20060101
H04W036/32 |
Claims
1. A method for managing wireless communications, comprising:
identifying a subset of a set of neighboring cells for measurement
by a mobile device, the identification based on historical
information associated with mobility patterns of the mobile
device.
2. The method of claim 1, wherein the method is performed by a
network entity, the mobile device, or a combination of the two.
3. The method of claim 1, further comprising: receiving the
historical information from a server, the historical information
comprising a serving cell history of the mobile device over a
predetermined period of time collected by the server.
4. The method of claim 3, wherein the historical information
further comprises a history of neighboring cells for the mobile
device.
5. The method of claim 1, further comprising: collecting and
storing at the mobile device a serving cell history of the mobile
device over a predetermined period of time, the historical
information comprising the serving cell history.
6. The method of claim 5, further comprising: collecting and
storing at the mobile device a history of neighboring cells for the
mobile device, the historical information comprising the history of
neighboring cells.
7. The method of claim 1, wherein the subset comprises a single
neighboring cell, the method further comprising: measuring a signal
strength associated with the single neighboring cell; and
performing a handover or cell reselection of the mobile device to
the single neighboring cell when the signal strength is greater
than a threshold level.
8. The method of claim 7, further comprising: determining not to
perform measurements of neighboring cells other than the single
neighboring cell when the signal strength associated with the
single neighboring cell is greater than the threshold level.
9. The method of claim 1, wherein the identifying the subset
comprises: determining a quality metric for each of the neighboring
cells in the set, the subset comprising the neighboring cells that
have a quality metric greater than a threshold level.
10. The method of claim 9, wherein the quality metric of each
neighboring cell is based on at least a data rate associated with
the neighboring cell, or an ability of the neighboring cell to
perform offloading to an alternate radio access technology, or a
projected amount of time for which the mobile device will remain
connected to the neighboring cell.
11. The method of claim 9, further comprising: ranking the
neighboring cells in the subset according to their respective
quality metrics.
12. The method of claim 9, further comprising: determining a
confidence level for each of the neighboring cells in the set, the
quality metric of each cell being based on at least the confidence
level of that cell, the subset comprising the neighboring cells
that have a confidence level greater than a threshold level.
13. The method of claim 12 further comprising: identifying one of
the neighboring cells in the subset with a confidence level greater
than a threshold level; and performing a blind handover of the
mobile device to the one neighboring cell.
14. The method of claim 1, further comprising: determining a
frequency with which measurements are performed by the mobile
device for the neighboring cells based on the historical
information.
15. The method of claim 1, further comprising: excluding at least
one of the neighboring cells from the subset based at least on a
current speed of the mobile device and a signal strength of the at
least one of the neighboring cells.
16. The method of claim 15, wherein the at least one of the
neighboring cells is excluded based on a determination that
performing a handover to the at least one of the neighboring cells
will result in a ping pong effect.
17. The method of claim 1, further comprising: adjusting at least
one cell measurement associated with handover or reselection based
on the historical information.
18. The method of claim 1, further comprising: adjusting at least
one handover or reselection criterion parameter based on the
historical information.
19. The method of claim 1, further comprising: selectively enabling
or disabling an air interface of the mobile device based on the
historical information and a current location of the mobile
device.
20. The method of claim 1, wherein the mobility patterns of the
mobile device comprise a route and schedule between a first
location and a second location.
21. The method of claim 1, wherein the mobility patterns of the
mobile device comprise a location and a period of time during which
the mobile device remains at the location.
22. An apparatus for managing wireless communications, comprising:
a processor; and a memory in electronic communication with the
processor, the memory embodying instructions, the instructions
being executable by the processor to: identify a subset of a set of
neighboring cells for measurement by a mobile device, the
identification based on historical information associated with
mobility patterns of the mobile device.
23. The apparatus of claim 22, wherein the apparatus comprises at
least one of: a network entity or the mobile device.
24. The apparatus of claim 22, wherein the instructions are further
executable by the processor to: receive the historical information
from a server, the historical information comprising a serving cell
history of the mobile device over a predetermined period of time
collected by the server.
25. The apparatus of claim 24, wherein the historical information
further comprises a history of neighboring cells for the mobile
device.
26. The apparatus of claim 22, wherein the instructions are further
executable by the processor to: collect and store at the apparatus
a serving cell history of the mobile device over a predetermined
period of time, the historical information comprising the serving
cell history.
27. The apparatus of claim 26, wherein the instructions are further
executable by the processor to: collect and store at the apparatus
a history of neighboring cells for the mobile device, the
historical information comprising the history of neighboring
cells.
28. The apparatus of claim 22, wherein the subset comprises a
single neighboring cell and the instructions are further executable
by the processor to: measure a signal strength associated with the
single neighboring cell; and perform a handover or cell reselection
of the mobile device to the single neighboring cell when the signal
strength is greater than a threshold level.
29. The apparatus of claim 28, wherein the instructions are further
executable by the processor to: determine not to perform
measurements of neighboring cells other than the single neighboring
cell when the signal strength associated with the single
neighboring cell is greater than the threshold level.
30. The apparatus of claim 22, wherein the wherein the instructions
are further executable by the processor to identify the subset by:
determining a quality metric for each of the neighboring cells in
the set, the subset comprising the neighboring cells that have a
quality metric greater than a threshold level.
31. The apparatus of claim 30, wherein the quality metric of each
neighboring cell is based on at least a data rate associated with
the neighboring cell, or an ability of the neighboring cell to
perform offloading to an alternate radio access technology, or a
projected amount of time for which the mobile device will remain
connected to the neighboring cell.
32. The apparatus of claim 30, wherein the instructions are further
executable by the processor to: rank the neighboring cells in the
subset according to their respective quality metrics.
33. The apparatus of claim 30, wherein the instructions are further
executable by the processor to: determine a confidence level for
each of the neighboring cells in the set, the quality metric of
each cell being based on at least the confidence level of that
cell, the subset comprising the neighboring cells that have a
confidence level greater than a threshold level.
34. The apparatus of claim 33 wherein the instructions are further
executable by the processor to: identify one of the neighboring
cells in the subset with a confidence level greater than a
threshold level; and perform a blind handover of the mobile device
to the one neighboring cell.
35. The apparatus of claim 22, wherein the instructions are further
executable by the processor to: determine a frequency with which
measurements are performed by the mobile device for the neighboring
cells based on the historical information.
36. The apparatus of claim 22, wherein the instructions are further
executable by the processor to: exclude at least one of the
neighboring cells from the subset based at least on a current speed
of the mobile device and a signal strength of the at least one of
the neighboring cells.
37. The apparatus of claim 36, wherein the at least one of the
neighboring cells is excluded based on a determination that
performing a handover to the at least one of the neighboring cells
will result in a ping pong effect.
38. The apparatus of claim 22, wherein the instructions are further
executable by the processor to: adjust at least one cell
measurement associated with handover or reselection based on the
historical information.
39. The apparatus of claim 22, wherein the instructions are further
executable by the processor to: adjust at least one handover or
reselection criterion parameter based on the historical
information.
40. The apparatus of claim 22, wherein the instructions are further
executable by the processor to: selectively enable or disable an
air interface of the mobile device based on the historical
information and a current location of the mobile device.
41. The apparatus of claim 22, wherein the mobility patterns of the
mobile device comprise a route and schedule between a first
location and a second location.
42. The apparatus of claim 22, wherein the mobility patterns of the
mobile device comprise a location and a period of time during which
the mobile device remains at the location.
43. An apparatus for managing wireless communications, comprising:
means for identifying a subset of a set of neighboring cells for
measurement by a mobile device, the identification based on
historical information associated with mobility patterns of the
mobile device.
44. The apparatus of claim 43, wherein the apparatus comprises at
least one of: a network entity or the mobile device.
45. The apparatus of claim 43, further comprising: means for
receiving the historical information from a server, the historical
information comprising a serving cell history of the mobile device
over a predetermined period of time collected by the server.
46. The apparatus of claim 43, wherein the historical information
further comprises a history of neighboring cells for the mobile
device.
47. The apparatus of claim 43, further comprising: means for
collecting and storing at the mobile device a serving cell history
of the mobile device over a predetermined period of time, the
historical information comprising the serving cell history.
48. The apparatus of claim 43, further comprising: means for
collecting and storing at the mobile device a history of
neighboring cells for the mobile device, the historical information
comprising the history of neighboring cells.
49. The apparatus of claim 43, wherein the subset comprises a
single neighboring cell, the apparatus further comprising: means
for measuring a signal strength associated with the single
neighboring cell; and means for performing a handover or cell
reselection of the mobile device to the single neighboring cell
when the signal strength is greater than a threshold level.
50. The apparatus of claim 49, further comprising: means for
determining not to perform measurements of neighboring cells other
than the single neighboring cell when the signal strength
associated with the single neighboring cell is greater than the
threshold level.
51. The apparatus of claim 43, wherein the means for identifying
the subset comprises: means for determining a quality metric for
each of the neighboring cells in the set, the subset comprising the
neighboring cells that have a quality metric greater than a
threshold level.
52. The apparatus of claim 51, wherein the quality metric of each
neighboring cell is based on at least a data rate associated with
the neighboring cell, or an ability of the neighboring cell to
perform offloading to an alternate radio access technology, or a
projected amount of time for which the mobile device will remain
connected to the neighboring cell.
53. The apparatus of claim 51, further comprising: means for
ranking the neighboring cells in the subset according to their
respective quality metrics.
54. The apparatus of claim 51, further comprising: means for
determining a confidence level for each of the neighboring cells in
the set, the quality metric of each cell being based on at least
the confidence level of that cell, the subset comprising the
neighboring cells that have a confidence level greater than a
threshold level.
55. The apparatus of claim 54 further comprising: means for
identifying one of the neighboring cells in the subset with a
confidence level greater than a threshold level; and means for
performing a blind handover of the mobile device to the one
neighboring cell.
56. The apparatus of claim 43, further comprising: means for
determining a frequency with which measurements are performed by
the mobile device for the neighboring cells based on the historical
information.
57. The apparatus of claim 43, further comprising: means for
excluding at least one of the neighboring cells from the subset
based at least on a current speed of the mobile device and a signal
strength of the at least one of the neighboring cells.
58. The apparatus of claim 57, wherein the at least one of the
neighboring cells is excluded based on a determination that
performing a handover to the at least one of the neighboring cells
will result in a ping pong effect.
59. The apparatus of claim 43, further comprising: means for
adjusting at least one cell measurement associated with handover or
reselection based on the historical information.
60. The apparatus of claim 43, further comprising: means for
adjusting at least one handover or reselection criterion parameter
based on the historical information.
61. The apparatus of claim 43, further comprising: means for
selectively enabling or disabling an air interface of the mobile
device based on the historical information and a current location
of the mobile device.
62. The apparatus of claim 43, wherein the mobility patterns of the
mobile device comprise a route and schedule between a first
location and a second location.
63. The apparatus of claim 43, wherein the mobility patterns of the
mobile device comprise a location and a period of time during which
the mobile device remains at the location.
64. A computer program product for managing wireless
communications, the computer program product comprising a
non-transitory computer-readable storage medium comprising
instructions executable by a processor to: identify a subset of a
set of neighboring cells for measurement by a mobile device, the
identification based on historical information associated with
mobility patterns of the mobile device.
Description
CROSS-REFERENCE
[0001] The present application claims priority to U.S. Provisional
Patent Application No. 61/860,789, filed Jul. 31, 2013, entitled
"PREDICTIVE MOBILITY IN CELLULAR NETWORKS," the entire disclosure
of which is incorporated herein by reference for all purposes.
BACKGROUND
[0002] The present description relates generally to wireless
communication, and more specifically to adapting the behavior of
mobile devices based on observed mobility trends. Wireless
communications systems are widely deployed to provide various types
of communication content such as voice, video, packet data,
messaging, broadcast, and so on. These systems may be
multiple-access systems capable of supporting communication with
multiple users by sharing the available system resources (e.g.,
time, frequency, space and power). Examples of such multiple-access
systems include code-division multiple access (CDMA) systems,
time-division multiple access (TDMA) systems, frequency-division
multiple access (FDMA) systems, and orthogonal frequency-division
multiple access (OFDMA) systems.
[0003] Generally, a wireless multiple-access communications system
may include a number of base stations, each simultaneously
supporting communication for multiple mobile devices. Base stations
may communicate with mobile devices on downstream and upstream
links. Each base station has a coverage range, which may be
referred to as the coverage area of the cell.
[0004] When a mobile device connected to a base station of a first
cell moves out of the coverage area of the first cell, the first
cell typically requests signal strength measurements for all
neighboring cells of the mobile device for use in identifying a
handover target candidate. These signal strength measurements and
reports may consume power, thereby reducing the battery life of the
mobile device. Additionally, these signal strength measurements and
reports may introduce delays into the handover process, thereby
increasing the likelihood that a call or connection is lost during
the handover. In addition, significant signaling resources are used
in communicating the measurement requests and reports between the
base stations and the mobile device before and during the handover
process.
[0005] While a mobile device in idle mode (i.e. a mode where the
device is camping on the cell and not actively communicating
information with the base station) does not communicate
measurements to the network, the mobile device may still monitor
signal strength from neighboring cells so as to identify good
candidates for reselection. This monitoring may consume a
significant percentage of the mobile device's power
consumption.
SUMMARY
[0006] The described features generally relate to one or more
improved systems, methods, and/or apparatuses for predictive
mobility in cellular networks. Further scope of the applicability
of the described methods and apparatuses will become apparent from
the following detailed description, claims, and drawings. The
detailed description and specific examples are given by way of
illustration only, since various changes and modifications within
the spirit and scope of the description will become apparent to
those skilled in the art.
[0007] According to a first set of illustrative embodiments, a
method for managing wireless communications, may include
identifying a subset of a set of neighboring cells for measurement
by a mobile device, the identification based on historical
information associated with mobility patterns of the mobile
device.
[0008] In certain examples, the method may be performed by a
network entity, the mobile device, or a combination of the two.
[0009] In certain examples, the historical information may be
received from a server, and the historical information may include
a serving cell history of the mobile device over a predetermined
period of time collected by the server. The historical information
may further include a history of neighboring cells for the mobile
device.
[0010] In certain examples, the mobile device may collect and store
a serving cell history of the mobile device over a predetermined
period of time, and the historical information may include the
serving cell history. The mobile device may further collect and
store a history of neighboring cells for the mobile device, and the
historical information may further include the history of
neighboring cells.
[0011] In certain examples, the subset may include a single
neighboring cell. A signal strength associated with the single
neighboring cell may be measured, and a handover or cell
reselection of the mobile device to the single neighboring cell may
be performed when the signal strength is greater than a threshold
level. The mobile device may determine not to perform measurements
of neighboring cells other than the single neighboring cell when
the signal strength associated with the single neighboring cell is
greater than the threshold level.
[0012] In certain examples, identifying the subset may include
determining a quality metric for each of the neighboring cells in
the set, the subset including the neighboring cells that have a
quality metric greater than a threshold level. The quality metric
of each neighboring cell is based on at least a data rate
associated with the neighboring cell, or an ability of the
neighboring cell to perform offloading to an alternate radio access
technology, or a projected amount of time for which the mobile
device will remain connected to the neighboring cell. The
neighboring cells in the subset may be ranked according to their
respective quality metrics.
[0013] In certain examples, a confidence level may be determined
for each of the neighboring cells in the set. The quality metric of
each cell may be based on at least the confidence level of that
cell, and the subset may include the neighboring cells that have a
confidence level greater than a threshold level. In certain
examples, one of the neighboring cells in the subset with a
confidence level greater than a threshold level may be identified,
and a blind handover of the mobile device to the one neighboring
cell may be performed.
[0014] In certain examples, a frequency with which measurements are
performed by the mobile device for the neighboring cells may be
determined based on the historical information.
[0015] In certain examples, at least one of the neighboring cells
may be excluded from the subset based at least on a current speed
of the mobile device and a signal strength of the at least one of
the neighboring cells. The at least one of the neighboring cells
may be excluded based on a determination that performing a handover
to the at least one of the neighboring cells will result in a ping
pong effect.
[0016] In certain examples, at least one cell measurement
associated with handover or reselection may be adjusted based on
the historical information.
[0017] In certain examples, at least one handover or reselection
criterion parameter may be adjusted based on the historical
information.
[0018] In certain examples, an air interface of the mobile device
may be selectively enabled or disabled based on the historical
information and a current location of the mobile device.
[0019] In certain examples, the mobility patterns of the mobile
device may include a route and schedule between a first location
and a second location. Additionally or alternatively, the mobility
patterns of the mobile device may include a location and a period
of time during which the mobile device remains at the location.
[0020] According to a second set of illustrative embodiments, an
apparatus for managing wireless communications, includes a
processor and a memory in electronic communication with the
processor. The memory may embody instructions, the instructions
being executable by the processor to identify a subset of a set of
neighboring cells for measurement by a mobile device, the
identification based on historical information associated with
mobility patterns of the mobile device.
[0021] In certain examples, the instructions may be executable by
the processor to perform one or more aspects of the functionality
described above with respect to the first set of illustrative
embodiments.
[0022] According to a third set of illustrative embodiments, an
apparatus for managing wireless communications includes means for
identifying a subset of a set of neighboring cells for measurement
by a mobile device, the identification based on historical
information associated with mobility patterns of the mobile
device.
[0023] In certain examples, the apparatus may further include means
for performing one or more aspects of the functionality described
above with respect to the first set of illustrative
embodiments.
[0024] According to a fourth set of illustrative embodiments, a
computer program product for managing wireless communications
includes a non-transitory computer-readable storage medium having
instructions executable by a processor to identify a subset of a
set of neighboring cells for measurement by a mobile device, the
identification based on historical information associated with
mobility patterns of the mobile device.
[0025] In certain examples, the instructions may be further
executable by the processor to perform one or more aspects of the
functionality described above with respect to the first set of
illustrative embodiments.
BRIEF DESCRIPTION OF THE DRAWINGS
[0026] A further understanding of the nature and advantages of the
present invention may be realized by reference to the following
drawings. In the appended figures, similar components or features
may have the same reference label. Further, various components of
the same type may be distinguished by following the reference label
by a dash and a second label that distinguishes among the similar
components. If only the first reference label is used in the
specification, the description is applicable to any one of the
similar components having the same first reference label
irrespective of the second reference label.
[0027] FIG. 1 shows a block diagram of a wireless communications
system, according to one aspect of the principles described
herein;
[0028] FIG. 2 shows a diagram of an example of device mobility in a
wireless communications system, according to one aspect of the
principles described herein;
[0029] FIGS. 3A-3C show a diagrams of other examples of device
mobility in a wireless communications system, according to one
aspect of the principles described herein;
[0030] FIG. 4 shows a diagram of an example of communications
between devices associated with a handover in a wireless
communications system, according to one aspect of the principles
described herein;
[0031] FIG. 5 shows a diagram of an example of communications
between devices associated with a handover in a wireless
communications system, according to one aspect of the principles
described herein;
[0032] FIG. 6 shows a diagram of an example of communications
between devices associated with a handover in a wireless
communications system, according to one aspect of the principles
described herein;
[0033] FIG. 7 shows a block diagram of a wireless communications
system, according to one aspect of the principles described
herein;
[0034] FIG. 8 shows a block diagram of a wireless communications
system, according to one aspect of the principles described
herein;
[0035] FIG. 9 shows a block diagram of one example of a mobile
device, according to one aspect of the principles described
herein;
[0036] FIG. 10 shows a block diagram of one example of a base
station, according to one aspect of the principles described
herein;
[0037] FIG. 11 shows a flowchart diagram of a method for managing
wireless communications, according to one aspect of the principles
described herein;
[0038] FIG. 12 shows a flowchart diagram of a method for managing
wireless communications, according to one aspect of the principles
described herein;
[0039] FIG. 13 shows a flowchart diagram of a method for managing
wireless communications, according to one aspect of the principles
described herein;
[0040] FIG. 14 shows a flowchart diagram of a method for managing
wireless communications, according to one aspect of the principles
described herein;
[0041] FIG. 15 shows a flowchart diagram of a method for managing
wireless communications, according to one aspect of the principles
described herein; and
[0042] FIG. 16 shows a flowchart diagram of a method for managing
wireless communications, according to one aspect of the principles
described herein.
DETAILED DESCRIPTION
[0043] Methods, systems, and devices are provided that may be used
to improve network and/or mobile device performance based on
learning and predicting the behavior of a mobile device (e.g.,
mobile phone, laptop, tablet, etc.) user. For a mobile device user,
for example, using predictive behavior may involve identifying a
subset of one or more neighboring cells for measurement by the
mobile device using historical information associated with mobility
patterns of the mobile device. These measurements may then be used
to hand off the mobile device to the identified (i.e., predicted)
cell as part of a handover or a cell reselection, for example.
[0044] Thus, the following description provides examples, and is
not limiting of the scope, applicability, or configuration set
forth in the claims. Changes may be made in the function and
arrangement of elements discussed without departing from the spirit
and scope of the disclosure. Various embodiments may omit,
substitute, or add various procedures or components as appropriate.
For instance, the methods described may be performed in an order
different from that described, and various steps may be added,
omitted, or combined. Also, features described with respect to
certain embodiments may be combined in other embodiments.
[0045] Techniques described herein may be used for various wireless
communications systems such as CDMA, TDMA, FDMA, OFDMA, SC-FDMA,
and other systems. The terms "system" and "network" are often used
interchangeably. A CDMA system may implement a radio technology
such as CDMA2000, Universal Terrestrial Radio Access (UTRA), etc.
CDMA2000 covers IS-2000, IS-95, and IS-856 standards. IS-2000
Releases 0 and A are commonly referred to as CDMA2000 1X, 1X, etc.
IS-856 (TIA-856) is commonly referred to as CDMA2000 1xEV-DO, High
Rate Packet Data (HRPD), etc. UTRA includes Wideband CDMA (WCDMA)
and other variants of CDMA. A TDMA system may implement a radio
technology such as Global System for Mobile Communications (GSM).
An OFDMA system may implement a radio technology such as Ultra
Mobile Broadband (UMB), Evolved UTRA (E-UTRA), IEEE 802.11 (Wi-Fi),
IEEE 802.16 (WiMAX), IEEE 802.20, Flash-OFDMA, etc. UTRA and E-UTRA
are part of Universal Mobile Telecommunication System (UMTS). 3GPP
Long Term Evolution (LTE) and LTE-Advanced (LTE-A) are new releases
of UMTS that use E-UTRA. UTRA, E-UTRA, UMTS, LTE, LTE-A, and GSM
are described in documents from an organization named "3rd
Generation Partnership Project" (3GPP). CDMA2000 and UMB are
described in documents from an organization named "3rd Generation
Partnership Project 2" (3GPP2). The techniques described herein may
be used for the systems and radio technologies mentioned above as
well as other systems and radio technologies. The description
below, however, describes an LTE system for purposes of example,
and LTE terminology is used in much of the description below,
although the techniques are applicable beyond LTE applications.
[0046] FIG. 1 is a block diagram conceptually illustrating an
example of a wireless communications system 100, in accordance with
an aspect of the present disclosure. The wireless communications
system 100 includes base stations (or cells) 105, mobile devices
115, and a core network 130. The base stations 105 may communicate
with the mobile devices 115 under the control of a base station
controller (not shown), which may be part of the core network 130
or the base stations 105 in various embodiments. Base stations 105
may communicate control information and/or user data with the core
network 130 through backhaul links 132. In certain embodiments, the
base stations 105 may communicate, either directly or indirectly,
with each other over backhaul links 134, which may be wired or
wireless communication links. The wireless communications system
100 may support operation on multiple carriers (waveform signals of
different frequencies). Multi-carrier transmitters can transmit
modulated signals simultaneously on the multiple carriers. For
example, each communication link 125 may be a multi-carrier signal
modulated according to the various radio technologies described
above. Each modulated signal may be sent on a different carrier and
may carry control information (e.g., reference signals, control
channels, etc.), overhead information, data, etc.
[0047] The base stations 105 may wirelessly communicate with the
mobile devices 115 via one or more base station antennas. Each of
the base stations 105 sites may provide communication coverage for
a respective coverage area 110. In some embodiments, base stations
105 may be referred to as a base transceiver station, a radio base
station, an access point, a radio transceiver, a basic service set
(BSS), an extended service set (ESS), a NodeB, eNodeB, Home NodeB,
a Home eNodeB, or some other suitable terminology. The coverage
area 110 for a base station may be divided into sectors making up
only a portion of the coverage area (not shown). The wireless
communications system 100 may include base stations 105 of
different types (e.g., macro, micro, and/or pico base stations).
There may be overlapping coverage areas for different
technologies.
[0048] In certain embodiments, the wireless communications system
100 is an LTE/LTE-A network communication system. In LTE/LTE-A
network communication systems, the terms evolved Node B (eNodeB)
may be generally used to describe the base stations 105. The
wireless communications system 100 may be a Heterogeneous LTE/LTE-A
network in which different types of eNodeBs provide coverage for
various geographical regions. For example, each eNodeB 105 may
provide communication coverage for a macro cell, a pico cell, a
femto cell, and/or other types of cell. A macro cell generally
covers a relatively large coverage area (e.g., several kilometers
in radius) and may allow unrestricted access by UEs 115 with
service subscriptions with the network provider. A pico cell would
generally cover a relatively smaller coverage area (e.g.,
buildings) and may allow unrestricted access by UEs 115 with
service subscriptions with the network provider. A femto cell would
also generally cover a relatively small coverage area (e.g., a
home) and, in addition to unrestricted access, may also provide
restricted access by UEs 115 having an association with the femto
cell (e.g., UEs 115 in a closed subscriber group (CSG), UEs 115 for
users in the home, and the like). An eNodeB 105 for a macro cell
may be referred to as a macro eNodeB. An eNodeB 105 for a pico cell
may be referred to as a pico eNodeB. And, an eNodeB 105 for a femto
cell may be referred to as a femto eNodeB or a home eNodeB. An
eNodeB 105 may support one or multiple (e.g., two, three, four, and
the like) cells.
[0049] The core network 130 may communicate with the base stations
105 via a backhaul link 132 (e.g., Si interface, etc.). The base
stations 105 may also communicate with one another, e.g., directly
or indirectly via backhaul links 134 (e.g., X2 interface, etc.)
and/or via backhaul links 132 (e.g., through core network 130). The
wireless communications system 100 may support synchronous or
asynchronous operation. For synchronous operation, the base
stations 105 may have similar frame timing, and transmissions from
different base stations 105 may be approximately aligned in time.
For asynchronous operation, the base stations 105 may have
different frame timing, and transmissions from different base
stations 105 may not be aligned in time. The techniques described
herein may be used for either synchronous or asynchronous
operations.
[0050] The mobile devices 115 may be dispersed throughout the
wireless communications system 100, and each mobile device 115 may
be stationary or mobile. A mobile device 115 may also be referred
to by those skilled in the art as a UE, mobile station, a
subscriber station, a mobile unit, a subscriber unit, a wireless
unit, a remote unit, a mobile device, a wireless communications
device, a remote device, a mobile subscriber station, an access
terminal, a mobile terminal, a wireless terminal, a remote
terminal, a handset, a user agent, a mobile client, a client, or
some other suitable terminology. A mobile device 115 may be a
cellular phone, a personal digital assistant (PDA), a wireless
modem, a wireless communication device, a handheld device, a tablet
computer, a laptop computer, a cordless phone, a wireless local
loop (WLL) station, or the like.
[0051] The communication links 125 shown in the wireless
communications system 100 may include uplink (UL) transmissions
from a mobile device 115 to a base station 105, and/or downlink
(DL) transmissions, from a base station 105 to a mobile device 115.
The downlink transmissions may also be called forward link
transmissions while the uplink transmissions may also be called
reverse link transmissions.
[0052] Mobile device 115 users typically have predictable behavior,
often doing the same things or going to the same places at about
the same time each day. One example is the travel pattern and
schedule of a mobile device 115 user going to and from work. The
user may typically leave home at a certain time, travel certain
roads to get to work, stay at work until it is time to go back home
using the same roads as before, and then repeat more or less the
same routine the next day. Because the movements of mobile device
115 user in such a scenario can be foreseeable, it may be possible
to predict with a high degree of confidence which cells are used by
the mobile device 115 at particular times when going to work, when
returning home at the end of the day, or even when taking a lunch
break. This prediction may be based on previous measurements, cell
reselections (e.g., when the mobile device 115 is in idle mode),
and/or handovers, which were performed by the mobile device 115
during the user's commute. Moreover, the use of predictive behavior
may also apply to other devices such as laptops, tablets, pads,
machine-to-machine (M2M) devices, and the like.
[0053] The ability to learn and predict the behavior of the mobile
device 115 user may not only be used to reduce the signaling that
is needed on the network side, but may also be used to reduce the
(usually large) number of measurements of neighboring cells made by
the mobile device 115 to determine a suitable cell for handover.
Reducing the number of measurements (and related reporting
messaging) may have the benefit of extending the battery life of
the mobile device 115. In dense urban areas, for example, where
large numbers of small cells and/or WiFi hot spots are deployed,
predicting the mobile device 115 mobility (e.g., pattern and
schedule) may have an impact on the performance of both the network
and the mobile device 115.
[0054] In addition to the commuting example described above, there
may be other instances in which the behavior of the mobile device
115 user may be leveraged to predict cells and reduce network
signaling and/or mobile device 115 measurements. One example is
when "airplane mode" is turned off after the user arrives at her
destination. When such a trip is routine and the behavior
predictable, the mobile device 115 may start by identifying a cell
at the place of arrival instead of looking (unsuccessfully) for
cells at the place of departure as it would typically do.
[0055] In yet another example of predictive behavior, when a cell
that is typically used by a mobile device during the user's commute
to work is congested, the network may look at other cells and may
use predictive techniques and the loading levels on the other cells
to identify a suitable cell for handover (or cell reselection when
the mobile device 115 is in idle mode, e.g., camping on the
network). Moreover, when the network knows that the mobile device
115 is going to use a particular cell at a certain time it may try
to schedule appropriate resources to be available for the mobile
device 115.
[0056] In still other examples of predictive behavior, the mobile
device 115 may selectively enable or disable one or more air
interfaces based on the historical information and/or a current
location of the mobile device. In certain examples, the mobile
device 115 may disable all air interfaces (e.g., enter airplane
mode) when the mobile device 115 follows a known path to a certain
location (e.g., the airport) in accordance with historical
patterns. Additionally or alternatively, a multi-mode mobile device
115 may selectively disable specific air interfaces (e.g., a
WLAN/WiFi interface, an LTE interface, a 1X/EV-DO interface, etc.)
based on the historical information and a current location of the
mobile device 115.
[0057] Generally, predictive mobility in wireless networks may be
used to alleviate network signaling demands, to reduce mobile
device 115 measurements to extend battery life, and/or to allocate
networking resources more effectively, for example.
[0058] FIG. 2 shows a diagram of a simplified example of device
mobility in a wireless communications system 200, according to one
aspect of the principles described herein. In the wireless
communications system 200 of FIG. 2, a mobile device 115-a travels
along a path 205 through the coverage areas 110-a, 110-b, 110-c,
110-d of a first base station 105-a, a second base station 105-b, a
third base station 105-c, and a fourth base station 105-d. The
mobile device 115-a may be an example of one or more of the mobile
devices 115 of FIG. 1. Similarly, the base stations 105 of FIG. 2
may be examples of one or more of the base stations 105 of FIG.
1.
[0059] Each base station 105 may represent an actual or potential
serving cell for the mobile device 115-a. In the present example,
the mobile device 115-a may begin at position 1 with the first base
station 105-a as the serving cell, then move through the coverage
area 110-a of the first base station 105-a to position 2. At
position 2, the mobile device 115-a may be located at the outer
reaches of the coverage area 110-a of the first base station 105-a
and enter an intersection of the coverage areas 110-a, 110-b, 110-c
of the first, second, and third base stations 105-a, 105-b, 105-c.
At position 2, the mobile device 115-a may report a signal strength
measurement of the first base station 105-a, the current serving
cell, to the first base station 105-a.
[0060] In conventional systems, if the mobile device 115-a is in
connected mode with the first base station 105-a, the signal
strength measurement of the first base station 105-a may indicate
that the mobile device 115-a is exiting the coverage area 110-a of
the first base station 105-a and trigger preparations for a
handover of the mobile device 115-a from the first base station
105-a to a new serving cell base station. Accordingly, the first
base station 105-a may instruct the mobile device 115-a to measure
the signal strengths of neighboring base stations to identify a
handover candidate for the mobile device 115-a. The mobile device
115-a may identify the neighboring base stations 105-b, 105-c using
a stored neighboring cell list (NCL) and/or by scanning for the
neighboring base stations 105-b, 105-c. If the mobile device 115-a
is in idle mode, the mobile device 115-a may measure neighboring
cells to identify a reselection target based on a pre-defined
threshold for the serving cell signal strength, as configured by
the carrier.
[0061] The mobile device 115-a may transmit signal strength
measurements to the serving base station 105-a, and the serving
base station 105-a may select either the second base station 105-b
or the third base station 105-c as the handover target base station
for the mobile device 115-a based on the signal strength
measurements. If the second base station 105-b is selected as the
handover target, the mobile device 115-a might briefly handover to
the second base station 105-b, and then perform an additional
handover to the third base station 105-c as the mobile device 115-a
moves out of the coverage area 110-b of the second base station
105-b. In certain examples, upon arriving at position 3, the mobile
device 115-a may be handed over to the fourth base station 105-d
(e.g., a femtocell or picocell) before returning to the third base
station 105-c.
[0062] In such systems, it may be difficult for the current serving
cell and the mobile device 115-a to determine the optimal time to
perform a handover, and the most appropriate handover target. For
example, at position 2, a more efficient transition may be for the
mobile device 115-a to bypass the second base station 105-b and
move directly from the first base station 105-a to the third base
station 105-c. Similarly, when the mobile device 115-a is at
position 3, the signal strength of the fourth base station 105-d
may be stronger than that of the third base station 105-c for a
short amount of time, but as the mobile device 115-a is moving
along the path 205 (e.g., in a train or automobile), the mobile
device 115-a may spend a small amount of time in the coverage area
110-d of the fourth base station 105-d, thereby triggering another
handover in short order. In certain examples, the mobile device
115-a may exit the coverage area 110-d of the fourth base station
105-d before there is an opportunity to complete a handover to the
next serving cell, which may result in a dropped call or
interrupted data connectivity. Thus, it may be more efficient to
refrain from handing the mobile device 115-a over to the fourth
base station 105-d when it can be determined that the mobile device
115-a is traveling along the path 205.
[0063] To address these and other issues, the present description
provides methods, systems, and devices that may be used to improve
network and/or mobile device 115 performance based on learning and
predicting the behavior of the mobile device 115. Using predictive
behavior may involve identifying a neighboring cell for measurement
by using historical information associated with mobility patterns
of the mobile device 115. These measurements may then be used to
hand off the mobile device 115 to the identified (i.e., predicted)
cell as part of a handover or a cell reselection, for example.
[0064] In the example of FIG. 2, for example, the mobile device
115-a may regularly travel along path 205 at regular intervals,
times of day, and at consistent speeds. This behavior may be
tracked and stored at the mobile device 115-a, a network server,
and/or one or more of the base stations 105. Based on the
historical information, the mobile device 115-a and/or a current
serving base station can predict a next location of the mobile
device 115-a, using the predicted next location to inform the
selection of handover and reselection targets. For example, when
the mobile device 115-a approaches position 2, the first base
station 105-a-2 may determine, from the current location and speed
of the mobile device 115-a in relation to stored historic data
related to mobility patterns of the mobile device 115-a, that the
mobile device 115-a is likely traveling along path 205.
[0065] Accordingly, the first base station 105-a may determine that
the mobile device 115-a is moving more into the coverage area of
the third base station 105-c than the second base station 105-b.
Based on a level of confidence in that prediction, the base station
105-a may instruct the mobile device 115-a to only measure the
signal strength of the third base station 105-c (i.e., rather than
all neighboring base stations 105) and, if the signal strength of
the third base station 105-c is satisfactory, select the third base
station 105-c as the handover target without considering other
neighboring base stations 105 as possible handover targets.
[0066] Similarly, when the mobile device 115-a approaches position
3 at the fringes of the coverage area 110-c of the third base
station 105-c, the third base station 105-c and/or mobile device
115-a may determine, based on the historic data related to the
mobility patterns of the mobile device 115-a, that the mobile
device 115-a is likely on the known path 205. Accordingly, the
third base station 105-c and/or mobile device 115-a may determine
that the fourth base station 105-d is an inappropriate handover
target for the mobile device 115-a. This determination may be based
on the prediction that the mobile device 115-a will continue along
path 205, the current speed of the mobile device 115-a, and the
known cell edge signal strength of the coverage area 110-d of the
fourth base station 105-d. Accordingly, the third base station
105-c and/or the mobile device 115-a may choose to exclude the
fourth base station 105-d from signal strength measurements made at
the mobile device 115-a to select a handover target.
[0067] FIGS. 3A-3C show diagrams examples of device mobility in a
wireless communications system 300, according to aspects of the
principles described herein. Specifically, FIGS. 3A-3C illustrate
an illustrative path 205-a of a mobile device 115-b between a
user's home location 305 and the user's work location 310. The path
205-a may traverse the coverage areas 110 of a number of large
cells and small cells.
[0068] When behavioral information is not considered, the user may
travel from the home location 305 to the work location 310 along
the depicted path 205-a in a normal manner. For example, when the
current serving cell signal strength measurement drops, the mobile
device 115-b may notify the network, which in turn may provide a
neighboring cell list (NCL) for the mobile device 115-b to take
measurements and report the strongest cell.
[0069] Referring specifically to FIG. 3A, after the signal strength
drops in cell 1, the mobile device 115-b may find cell 2 the
strongest and the network may ask the mobile device 115-b to
hand-off to cell 2. The same process may take place with cells 3,
4, 5, 6, 7, 8, 9, and 10 until the user reaches the work location
310. Before each handover, however, the mobile device 115-b may
make measurements of all the neighboring cells requested by the
network even though the same handful of cells is used each day.
Moreover, the mobile device 115-b may traverse clusters of
femtocells or other small cells (e.g., cells 5, 6, and 10) having
small cell radiuses along the path 205-a, which may result in a
ping pong effect in which the mobile device 115-b is repeatedly
handed over to or from the same set of one or more cells. To
overcome these inefficiencies, predictive behavior of the mobile
device 115 may be leveraged in a number of ways.
[0070] According to a first approach, a predictive algorithm
application may reside on the mobile device 115-b. Mobile device
profile information (i.e., based on collected historical
information associated with mobility patterns of the mobile device)
may be stored by the mobile device 115-b for use by the predictive
algorithm application. Over a certain learning period (e.g., twenty
days), enough information (e.g., location, time, speed, cell
measurements, etc.) may be collected by the mobile device 115-b to
predict with a high degree of confidence where the mobile device
115 will be on a certain day and time. Alternatively, a network
entity (e.g., measurement server) may collect and store the profile
information of the mobile device 115-b, and the predictive
algorithm application of the mobile device 115-b may communicate
with the network entity to access the mobile device profile
information.
[0071] When the signal strength drops in cell 1 of FIG. 3A, the
predictive algorithm application may identify with a high degree of
confidence (e.g., >90%) that the mobile device 115-b is moving
along a known path 205-a and that the next cell along the path
205-a to the work location 310 is cell 2. The network, not aware of
the mobile device 115 behavior, may instruct the mobile device
115-b to make measurements of all neighboring cells in a NCL.
[0072] Because of the high degree of confidence that cell 2 is the
next cell, the mobile device 115-b may only measure cell 2 and
report the measurements of cell 2 to the network before proceeding
with a handover to cell 2. Alternatively, the mobile device 115-b
may make measurements on a reduced subset of neighboring cells
(e.g., a ranked reduced set) found in the NCL. In certain examples,
the profile information for the mobile device 115-b may include a
history of neighboring cells (e.g., both serving cells and
non-serving cells along the path 205-a) for the mobile device
115-b, and the reduced subset of the neighboring cells may be
identified based on the history of neighboring cells.
[0073] In addition to identifying the reduced subset of the
neighboring cells for measurement by the mobile device 115-b, the
mobile device 115-b may also select a frequency with which the
measurements are made and/or a type of measurement to perform based
on the profile information. The types of measurements taken by the
mobile device 115-f and determined by the profile information may
include serving and neighboring cell radio frequency (RF)
measurements, including carrier frequencies, physical cell IDs,
location, signal strength measurements (e.g., RSCP, RSRQ, RSRP),
time measurements, and the like.
[0074] Fewer cells to measure may result in simplified signaling
and increased battery life for the mobile device 115-b. In the
event the mobile device 115-b does not find the predicted next cell
and/or the reduced set of cells, the mobile device 115-b and/or
network may fall back to the conventional operation of measuring
the full set of neighboring cells. In certain examples, the
predicted next cell and/or reduced set of cells may not be found
during only a single event, a short period of time, or a deviation
from the route. Once the mobile device 115-b and/or network
confirms that the mobile device 115-b is back on the known path
205-a, the practice of measuring reduced sets of neighboring cells
along the predictive route may continue.
[0075] In a different scenario, the mobile device 115-b may be
attached to serving cell 1, and the predictive algorithm may
determine a confidence level of 60% that cell 2 is the next cell, a
confidence level of 20% that cell A is the next cell, and a
confidence level of 20% that cell B is the next cell, the mobile
device 115-b may elect to make measurements on cell 2, cell A, and
cell B as possible handover targets. If cell A or B is the
strongest, the mobile device 115-b may operate in its usual mode
without taking behavioral information into account. If cell 2 is
the strongest, predictive behavior may be used when selecting cells
along the path 205-a.
[0076] In certain examples, the mobile device may recognize, based
on a prediction that the mobile device 115-b will remain on the
path 205-a, that certain handovers along the path may be
unnecessary. For example, as the mobile device 115-b travels within
cell 4, the mobile device 115-a may travel through the coverage
areas of cell 5 and cell 6, which may be femtocells. Nevertheless,
the mobile device 115-b may determine that handing over to one or
more of these femtocells may result in a ping pong effect, a
dropped call, or other loss of connectivity due to the small cell
radiuses of the femtocells and an estimated amount of time the
mobile device 115-b will be in each femtocell. Thus, based on the
historical information and current status of the mobile device
115-b, the mobile device 115-b may exclude cell 5 and cell 6 from
an identified subset of neighboring cells for which signal strength
measurements are to be performed. This decision may result in the
mobile device 115-b avoiding handovers to the femtocells while the
mobile device 115-b travels along the path 205-a.
[0077] In certain examples, where the mobile device 115-b is
measuring and storing the signal strength for each cell, the mobile
device 115-b may have the ability to create a mean and standard
deviation for the signal strength of each cell. The mean and
standard deviation values for each cell may allow the mobile device
115-b to remain on a cell or move forward with a hand-over to a
target cell when the signal strength of the serving cell is lower
than expected. For example, the path 205-a may include a train
crossing that occasionally delays travel along the path 205-a. The
mobile device 115-b may store or have access to 20 days of
historical route information, and during these 20 days a train may
have delayed the travel of the mobile device 115-b along the path
205-a 10 times. The train may pass between the mobile device 115-b
and the serving cell during this delay, causing the signal strength
of the serving cell to drop significantly, even though the mobile
device 115-b remains on the predicted path 205-a.
[0078] By tracking historical mean and standard deviation values
for the serving cell's signal strength, the predictive algorithm
application residing on the network and/or the mobile device 115-b
may identify that the drop in signal strength is a regular and
expected occurrence, thereby allowing the mobile device 115-b to
remain connected to the serving cell. In certain examples, the mean
and standard deviation values for the signal strength of a
particular cell may be used to calculate a quality metric
associated with that particular cell for use in handover and
reselection decisions.
[0079] According to a second approach, the predictive behavior of
the mobile device 115-b may be stored in a network entity (e.g.,
measurement server) and may be accessed by a predictive algorithm
in the network to optimize cell measurements and handover
procedures. One way in which behavior information may be collected
is by tracking the electronic serial number (ESN) or the
international subscriber identity (IMSI) through base stations
(e.g., NB/eNBs), mobility management entities (MMES), or other
network devices. Over the learning period profile information may
be collected by the network based on the observed behavior of the
mobile device 115-b. The profile information may be used to predict
with a high degree of confidence where a particular mobile device
115 will be on a certain day and time.
[0080] When the signal strength of a serving cell drops, the
predictive algorithm residing on the network may identify with a
high degree of confidence (e.g., >90%) the next cell in the path
205-a. The network, instead of providing a full NCL (which may
include up to 32 cells for measurements, for example), may instruct
the mobile device 115-b to make measurements on a reduced set of
cells (e.g., a ranked reduced set) or perhaps only on the predicted
next cell. Additionally or alternatively, the network may indicate
to the mobile device 115-b that one or more of the neighboring
cells have been blacklisted. The mobile device 115-b may then omit
the blacklisted neighboring cells. The network may select at least
one the blacklisted cells based on the historical profile
information associated with the mobile device 115-b. In certain
examples, one or more of the cells may be blacklisted when the
predictive algorithm determines that the mobile device 115-b is on
the path 205-a, but may not be blacklisted when the mobile device
115-b is on other known paths or not traveling on any known path.
The mobile device 115-b may report the requested measurements to
the network, and the process may proceed with a handover to the
predicted next cell.
[0081] In a different scenario, the mobile device 115-b may be
attached to serving cell 1, and the predictive algorithm may
determine a confidence level of 60% that cell 2 is the next cell, a
confidence level of 20% that cell A is the next cell, and a
confidence level of 20% that cell B is the next cell, the network
may instruct the mobile device 115-b to make measurements on those
three cells. If cell A or B is the strongest, the network and
mobile device 115-b may operate in their usual or conventional mode
without taking behavioral information into account. If cell 2 is
the strongest, predictive behavior may be used when selecting cells
along the path 205-a.
[0082] According to a third approach, the predictive behavior of
the mobile device 115-b may be stored in a network entity (e.g.,
measurement server) and may be accessed by both a predictive
algorithm application in the mobile device 115-b and a predictive
algorithm in the network. When both the mobile device 115-b and the
network determine that there is a high degree of confidence that
cell 2 is the next cell after the strength of cell 1 drops, the
mobile device 115-b and the network may perform a handover to cell
2 without requesting measurements of cell 2 and without reporting
measurements of cell 2 (e.g., a blind handover or blindoff).
[0083] FIG. 3B shows another example of the path 205-a between the
home location 305 and the work location 310. In certain examples,
because the mobile device 115-b may store profile information based
on collected historical information associated with mobility
patterns of the wireless device 115-b, the mobile device 115-b may
be able to skip certain cells along the path 205-a that the mobile
device 115-b would have otherwise reselected (e.g., based on
network defined thresholds) or handed over to (e.g., in response to
a handover request message from the network). The mobile device
115-b may elect to skip these cells based on a determination that
the value of handing over or reselecting to these cells is limited.
For example, the mobile device 115-b may determine that the time
that would be spent on a cell would be limited due to ping-ponging
between the cell and a neighboring cell. In particular, the mobile
device 115-b may perform this skipping during an idle mode, where
user plane data is not actively being transmitted or received at
the mobile device 115-b.
[0084] In some cases, a cell that the mobile device 115-b elects to
skip may have a higher received signal strength indicator (RSSI)
value than the current cell to which the mobile device 115-b is
connected. If the mobile device 115-b elects to skip a cell with a
higher RSSI value, the mobile device 115-b may move to a future
cell along the path 205-a (which may also have a lower RSSI value
than the cell being skipped) or remain connected to the current
cell.
[0085] In certain examples, the mobile device 115-b may adjust one
or more cell measurements along the path 205-a. The cell
measurement adjustments may include increasing the cell
measurements of one or more cells (e.g., to increase the likelihood
of selection as a handover or reselection target) and/or decreasing
the measurement of one or more cells (e.g., to decrease the
likelihood of selection as a handover or reselection target). For
example, if the mobile device 115-b elects to skip a cell along the
path 205-a, measurements taken by the mobile device 115-b of that
cell may be modified or biased such that a handover to or
reselection of that cell does not occur.
[0086] Additionally or alternatively, the mobile device 115-b may
adjust one or more handover or reselection criterion parameters to
affect under what conditions a handover will occur. For example,
the RSSI threshold triggering handover or reselection to one or
more cells may be increased (e.g., to decrease the likelihood of
selection as a handover or reselection target) or decreased (e.g.,
to increase the likelihood of selection as a handover or
reselection target). This modification of RSSI thresholds or other
handover or reselection criterion parameters may result in expanded
effective coverage areas 320 (indicated by dashed lines) for
selected cells along the path 205-a and/or reduced effective
coverage areas 320 for other cells along the path 205-a.
[0087] These modifications to the cell measurement adjustments
and/or the handover or reselection criterion parameters may be
chosen and enforced by the network, the mobile device 115-b, or
both.
[0088] In the example of FIG. 3B, the mobile device 115-b may,
based on the historical mobility patterns of the wireless device
115-b, determine that cells 1, 3, 7, and 9 may provide complete
coverage to the mobile device 115-b along the path 205-a if the
lower RSSI thresholds for handover and reselection are applied to
these cells. As shown in FIG. 3B, the expanded effective coverage
areas 320 of cells 1, 3, 7, and 9 may cover the entire path 205-a
between the home location 305 and the work location 310. This
reduction in the number of cells that the mobile device 115-b
connects to along the path 205-a may accordingly reduce the number
of measurements taken by the mobile device 115-b and handovers to
new cells, thereby reducing power consumption and increasing the
battery life of the mobile device 115-b and reducing the networking
signaling, especially network signaling associated with
handovers.
[0089] FIG. 3C shows another example of the path 205-a between the
home location 305 and the work location 310. In certain examples,
distinctive physical features of a given area may shape the
coverage area of a cell. For example, a street in a large urban
area lined with tall buildings may allow for enhanced propagation
of radio frequency signals along the corridor of the street. As
shown in FIG. 3C, for example, when taking into consideration a
lower RSSI threshold for handover and reselection, the expanded
effective coverage area 320 of cell 7 may be long and narrow along
a street. If the path 205-a runs along that street, the mobile
device 115-b may take advantage of the expanded effective coverage
areas 320 of cells 1, 7, and 9 to travel from the home location 305
to the work location 310 by connecting to only cells 1, 7, and 9.
The mobile device 115-b may elect to skip other cells traversed by
the path 205-a based on a determination that the mobile device
115-b is traveling along the path 205-a and that the value of
handing over or reselecting to these cells is limited.
[0090] FIG. 4 shows a diagram of another example of communications
between devices associated with a handover in a wireless
communications system 400, according to one aspect of the
principles described herein. The wireless communications system 400
of the present example includes a mobile device 115-c, a base
station 105-d associated with a first cell ("cell 1"), a base
station 105-e associated with a second cell ("cell 2"), and an
optional measurement server 401 configured to store historical
information 405 for the mobile device 115-c related to a mobility
profile of the mobile device 115-c. In certain embodiments, the
mobility profile of the mobile device may be stored entirely on the
mobile device 115-c. The wireless communications system 400 may be
an example of one or more of the wireless communications systems
100, 200, 300 described above with respect to the previous
Figures.
[0091] In the present example, a predictive algorithm application
410 may be executed by the base station 105-d of cell 1. The
predictive algorithm application 410-a of the mobile device 115-c
may store and retrieve historical information associated with
mobility patterns of the mobile device 115-c. As described above,
the historical information may be entirely stored on the mobile
device 115-c. Alternatively, the predictive algorithm application
410 of the mobile device 115-c may retrieve the historical
information associated with mobility patterns of the mobile device
115-c from the mobile device 115-c. The mobile device 115-c may
enter into a connected mode 412 with cell 1.
[0092] At block 415, the mobile device 115-c may measure the signal
strength of cell 1. The mobile device 115-c may transmit a report
420 to the base station 105-d of cell 1 indicating that the
received signal strength indication (RSSI) of cell 1 is low (e.g.,
below a threshold). Based on the historical information associated
with the mobile device 115-c, the base station 105-d of cell 1 may
determine that a handover is imminent and transmit a request 425 to
the mobile device 115-c to measure the signal strength of a
neighboring cell list (NCL) containing neighboring cells 2, A, and
B.
[0093] Based on the historical information associated with the
mobile device 115-c, the predictive algorithm application 410 of
the mobile device 115-c may determine with a confidence level
greater than a threshold (e.g., 90%) that the next cell for the
mobile device 115-c is cell 2. The mobile device 115-c may
therefore choose to measure the signal strengths of only cell 1 and
cell 2 at block 430, transmit a report 435 to the base station
105-d of cell 1 of the signal strength of cell 2, and the base
station 105-d of cell 1 may initiate a handover of the mobile
device 115-c to cell 2. The base station 105-d of cell 1 may then
work with the mobile device 115-c and the base station 105-e of
cell 2 to handover 440 the mobile device 115-c from cell 1 to cell
2, and the mobile device 115-c may enter a connected mode 445 with
cell 2.
[0094] FIG. 5 shows a diagram of an example of communications
between devices associated with a handover in a wireless
communications system 500, according to one aspect of the
principles described herein. The wireless communications system 500
of the present example includes a mobile device 115-d, a base
station 105-f associated with a first cell ("cell 1"), a base
station 105-g associated with a second cell ("cell 2"), and a
measurement server 401-a configured to store historical information
for the mobile device 115-d related to a mobility profile of the
mobile device 115-d. The wireless communications system 500 may be
an example of one or more of the wireless communications systems
100, 200, 300, 400 described above with respect to the previous
Figures.
[0095] In the present example, a predictive algorithm application
410-a is executed by the base station 105-f of cell 1. The base
station 105-f of cell 1 may communicate with the measurement server
401-a to store and retrieve historical information 515 associated
with mobility patterns of the mobile device 115-d. The mobile
device 115-d may enter into a connected mode 520 with cell 1.
[0096] At block 525, the mobile device 115-d may measure the signal
strength of cell 1, the serving cell. The mobile device 115-d may
transmit a report 530 to the base station 105-f of cell 1
indicating that the received signal strength indication (RSSI) of
cell 1 is low (e.g., below a threshold). Based on the historical
information associated with the mobile device 115-d, the base
station 105-f of cell 1 may use the predictive algorithm
application 410-a to determine with a confidence level greater than
a threshold (e.g., 90%) that the next cell for the mobile device
115-d is cell 2. Accordingly, the base station 105-f of cell 1 may
transmit a request 535 to the mobile device 115-d to measure the
signal strength of a neighboring cell list (NCL) containing only
cell 2. The base station 105-f may exclude all other neighboring
cells from the NCL.
[0097] The mobile device 115-d may measure the signal strengths of
cell 1 and cell 2 at block 540, transmit a report 545 to the base
station 105-f of cell 1 that the signal strength of cell 2 is
greater than a threshold level, and the base station 105-f of cell
1 may initiate a handover of the mobile device 115-d to cell 2. The
base station 105-f of cell 1 may then work with the mobile device
115-d and the base station 105-g of cell 2 to handover 550 the
mobile device 115-d from cell 1 to cell 2, and the mobile device
115-d may enter a connected mode 555 with cell 2.
[0098] FIG. 6 shows a diagram of another example of communications
between devices associated with a handover in a wireless
communications system 600, according to one aspect of the
principles described herein. The wireless communications system 600
of the present example includes a mobile device 115-e, a base
station 105-h associated with a first cell ("cell 1"), a base
station 105-i associated with a second cell ("cell 2"), and a
measurement server 401-b configured to store historical information
for the mobile device 115-e related to a mobility profile of the
mobile device 115-e. The wireless communications system 600 may be
an example of one or more of the wireless communications systems
100, 200, 300, 400, 500 described above with respect to the
previous Figures.
[0099] In the present example, predictive algorithm applications
410 are executed by both the base station 105-h of cell 1 and the
mobile device 115-e. The predictive algorithm applications 410 may
communicate with the measurement server 401-b to store and retrieve
historical information 605, 610 associated with mobility patterns
of the mobile device 115-e. The mobile device 115-e may enter into
a connected mode 615 with cell 1.
[0100] At block 620, the mobile device 115-e may measure the signal
strength of cell 1. The mobile device 115-e may transmit a report
625 to the base station 105-h of cell 1 indicating that the
received signal strength indication (RSSI) of cell 1 is low (e.g.,
below a threshold). Based on the historical information associated
with the mobile device 115-e, the predictive algorithm applications
410 of the base station 105-h and the mobile device 115-e may
determine that a handover is imminent and that, based on a
predictive analysis of the historical information related to the
mobility profile of the mobile device 115-e, that the cell 2 is the
next cell for the mobile device 115-e. Accordingly, the base
station 105-h of cell 1 may work with the mobile device 115-e and
the base station 105-i of cell 2 to perform a blind handover 630
the mobile device 115-e from cell 1 to cell 2, and the mobile
device 115-e may enter a connected mode 635 with cell 2.
[0101] FIG. 7 shows a block diagram of a wireless communications
system 700, according to one aspect of the principles described
herein. The wireless communications system 700 may include an
operations, administration and management (OAM) system 705, a
minimize drive test (MDT) server 401-c, a base station 105-j, and a
mobile device 115-E Each of these components may be in
communication, directly or indirectly. The wireless communications
system 700 may include aspects of one or more of the wireless
communications systems 100, 200, 300, 400, 500, 600 described above
with reference to the previous Figures.
[0102] The MDT server 401-c may be a server used by the network to
gather information used by network operators in evaluating network
performance. The MDT server 401-c may be an example of one or more
of the measurement servers 401 described above with reference to
FIGS. 4-6. Using the MDT server 401-c, measurements taken at a
mobile device 115-f in connected mode (immediate MDT) or idle mode
(logged MDT) may be requested from the mobile device 115-E The
types of measurements taken by the mobile device 115-f and
requested by the MDT server 401-c may include serving and
neighboring cell radio frequency (RF) measurements, including
carrier frequencies, physical cell IDs, location, signal strength
measurements (e.g., RSCP, RSRQ, RSRP), time measurements, and the
like.
[0103] The controller for the MDT functionality may reside in the
OAM system 705 of the network. The OAM system 705 may initiate and
control the MDT data collection processes by sending a message
activating the measurements and also including parameters for the
data collection to the base station 105-j. The base station 105-j
may then pass on the message to the mobile device 115-E After the
measurements are completed by the mobile device 115-f, the mobile
device 115-f may transmit the collected measurements to the base
station 105-j, and these measurements may then be forwarded to the
MDT server 401-c for storage and processing.
[0104] One or more MDT servers 401-c deployed in a network may be
used to store historical information for the mobile device 115-f
associated with mobility patterns of the mobile device 115-f. The
historical information for the mobile device 115-f may be gathered
and transmitted to the MDT server 401-c for storage. The historical
information may then be used by a predictive algorithm application
410-d running on the base station 105-j (as shown in FIG. 7) and/or
the mobile device 115-f (not shown) to identify a subset of a set
of neighboring cells for measurement by the mobile device 115-f
consistent with the foregoing principles. While the base station
105-j of FIG. 7 is shown running a predictive algorithm application
410-d, it will be understood that one or more of the base stations
105 gathering the historical information for the mobile device
115-f may not be running the predictive algorithm application
410-d.
[0105] FIG. 8 shows a block diagram of a wireless communications
system 800, according to one aspect of the principles described
herein. Specifically, FIG. 8 illustrates a design of a base station
105-k and a mobile device 115-g, in accordance with an aspect of
the present disclosure. The wireless communications system 800 may
illustrate aspects of one or more of the wireless communications
systems 100, 200, 300, 400, 500, 600, 700 described above with
reference to previous Figures. For example, the base station 105-k
may be an example of one or more of the base stations 105 described
above with respect to FIGS. 1-7, and the mobile device 115-g may be
an example of one or more of the mobile devices 115 described above
with respect to FIGS. 1-7.
[0106] The base station 105-k may be equipped with base station
antennas 834-1 through 834-x, where x is a positive integer, and
the mobile device 115-g may be equipped with mobile device antennas
852-1 through 852-n, where n is a positive integer. In the wireless
communications system 800, the base station 105-k may be able to
send data over multiple communication links at the same time. Each
communication link may be called a "layer" and the "rank" of the
communication link may indicate the number of layers used for
communication. For example, in a 2.times.2 MIMO system where base
station 105-k transmits two "layers," the rank of the communication
link between the base station 105-k and the mobile device 115-g is
two.
[0107] At the base station 105-k, a base station transmit processor
820 may receive data from a base station data source and control
information from a base station controller/processor 840. The
control information may be for the PBCH, PCFICH, PHICH, PDCCH, etc.
The data may be for the PDSCH, etc. The base station transmit
processor 820 may process (e.g., encode and symbol map) the data
and control information to obtain data symbols and control symbols,
respectively. The base station transmit processor 820 may also
generate reference symbols, e.g., for the PSS, SSS, and
cell-specific reference signal. An base station transmit (TX) MIMO
processor 830 may perform spatial processing (e.g., precoding) on
data symbols, control symbols, and/or reference symbols, if
applicable, and may provide output symbol streams to the base
station transmit modulators 832-1 through 832-x. Each base station
modulator 832 may process a respective output symbol stream (e.g.,
for OFDM, etc.) to obtain an output sample stream. Each base
station modulator 832 may further process (e.g., convert to analog,
amplify, filter, and upconvert) the output sample stream to obtain
a downlink (DL) signal. In one example, DL signals from base
station modulators 832-a through 832-x may be transmitted via the
base station antennas 834-a through 834-x, respectively.
[0108] At the mobile device 115-g, the mobile device antennas 852-1
through 852-n may receive the DL signals from the base station
105-k and may provide the received signals to the mobile device
demodulators 854-a through 854-n, respectively. Each mobile device
demodulator 854 may condition (e.g., filter, amplify, downconvert,
and digitize) a respective received signal to obtain input samples.
Each mobile device demodulator 854 may further process the input
samples (e.g., for OFDM, etc.) to obtain received symbols. A mobile
device MIMO detector 856 may obtain received symbols from all the
demodulators 854-a through 854-n, perform MIMO detection on the
received symbols if applicable, and provide detected symbols. A
mobile device receiver (Rx) processor 858 may process (e.g.,
demodulate, deinterleave, and decode) the detected symbols,
providing decoded data for the mobile device 115-g to a data
output, and provide decoded control information to a mobile device
processor 880, or mobile device memory 882.
[0109] On the uplink (UL), at the mobile device 115-g, a mobile
device transmit processor 864 may receive and process data from a
mobile device data source. The mobile device transmit processor 864
may also generate reference symbols for a reference signal. The
symbols from the mobile device transmit processor 864 may be
precoded by a mobile device transmit MIMO processor 866 if
applicable, further processed by the mobile device demodulators
854-a through 854-n (e.g., for SC-FDMA, etc.), and be transmitted
to the base station 105-k in accordance with the transmission
parameters received from the base station 105-k. At the base
station 105-k, the UL signals from the mobile device 115-g may be
received by the base station antennas 834, processed by the base
station demodulators 832, detected by a base station MIMO detector
836 if applicable, and further processed by a base station receive
processor 838. The base station receive processor 838 may provide
decoded data to a base station data output and to the base station
processor 840.
[0110] The components of the mobile device 115-g may, individually
or collectively, be implemented with one or more Application
Specific Integrated Circuits (ASICs) adapted to perform some or all
of the applicable functions in hardware. Each of the noted modules
may be a means for performing one or more functions related to
operation of the wireless communications system 800. Similarly, the
components of the base station 105-k may, individually or
collectively, be implemented with one or more Application Specific
Integrated Circuits (ASICs) adapted to perform some or all of the
applicable functions in hardware. Each of the noted components may
be a means for performing one or more functions related to
operation of the wireless communications system 800.
[0111] The communication networks that may accommodate some of the
various disclosed embodiments may be packet-based networks that
operate according to a layered protocol stack. For example,
communications at the bearer or Packet Data Convergence Protocol
(PDCP) layer may be IP-based. A Radio Link Control (RLC) layer may
perform packet segmentation and reassembly to communicate over
logical channels. A Medium Access Control (MAC) layer may perform
priority handling and multiplexing of logical channels into
transport channels. The MAC layer may also use Hybrid ARQ (HARQ) to
provide retransmission at the MAC layer to improve link efficiency.
At the Physical layer, the transport channels may be mapped to
Physical channels.
[0112] In one configuration, the base station 105-k may operate as
a serving base station 105-k for the mobile device 115-g, and may
include means for identifying a set of neighboring cells for
measurement by the mobile device 115-g, where the identification is
based on historical information associated with mobility patterns
of the mobile device 115-g. In one aspect, the aforementioned means
may be the base station controller/processor 840, the base station
memory 842, the base station transmit processor 820, base station
receiver processor 838, the base station modulators/demodulators
832, and the base station antennas 834 of the base station 105-k
configured to perform the functions recited by the aforementioned
means.
[0113] In an additional or alternative configuration, the mobile
device 115-g may include means for identifying a set of neighboring
cells for measurement by the mobile device 115-g, where the
identification is based on historical information associated with
mobility patterns of the mobile device 115-g. In one aspect, the
aforementioned means may be the mobile device controller/processor
880, the mobile device memory 882, the mobile device transmit
processor 864, mobile device receiver processor 858, the mobile
device modulators/demodulators 854, and the mobile device antennas
852 configured to perform the functions recited by the
aforementioned means.
[0114] FIG. 9 shows a block diagram of one example of a mobile
device 115-h, according to one aspect of the principles described
herein. The mobile device 115-h may be an example of one or more of
the mobile devices 115 described above with reference to the
previous Figures.
[0115] The mobile device 115-h of FIG. 9 may include a processor
910, a memory 915, a prediction module 920, a cell measurement
module 925, a handover module 930, and a wireless wide area network
(WWAN) radio 950. Each of these components may be in communication,
directly or indirectly.
[0116] The processor 910 may be configured to execute
computer-readable program code stored by the memory 915 to
implement one or more aspects of the prediction module 920, the
cell measurement module 925, the handover module 930, and/or the
wireless wide area network (WWAN) radio 950. The processor 910 may
also execute computer-readable program code stored by the memory
915 to implement other applications 917.
[0117] The prediction module 920 may be configured to implement the
functionality of one or more of the predictive algorithm
applications 410 described above with respect to the previous
Figures. In certain examples, the prediction module 920 may
identify a subset of a set of neighboring cells for measurement by
the mobile device 115-h based on historical information 919
associated with mobility patterns of the mobile device 115-h. The
subset may further be identified based on a current location or
state of the mobile device 115-h in relation to the historical
information 919. Additionally or alternatively, the prediction
module 920 may identify, based on the historical information 919,
an order in which measurements of neighboring cells are to be
performed (e.g., according to the likelihood of being the next
cell). In additional or alternative examples, the prediction module
920 may identify how frequently measurements of neighboring cells
are performed and/or the type of measurements to take.
[0118] In certain examples, a serving cell of the mobile device
115-h (e.g., a cell associated with one or more of the base
stations 105 described in other Figures of the present disclosure)
may identify the subset of the neighboring cells based on the
historical information 919, the order of measurements, the
frequency of measurements, and/or the type of measurements as
described above. In this case, the prediction module 920 may
determine this information based on signaling from the serving
cell. The mobile device 115-h may communicate with the serving cell
using the WWAN radio 950. In certain examples, the prediction
module 920 may communicate with a server (e.g., over WWAN radio
950) to receive the historical information 919. Additionally or
alternatively, the mobile device 115-h may collect and store the
historical information 919 locally in the memory 915 of the mobile
device 115-h, as shown in FIG. 9.
[0119] The historical information may include information about the
mobility patterns of the mobile device 115-h. The mobility patterns
may include, for example, a route and a schedule of the mobile
device 115-h between a first location and a second location.
Additionally or alternatively, the mobility patterns may include a
location and a period of time during which the mobile device 115-h
remains at the location. Thus, in certain examples, the historical
information may include a serving cell history of the mobile device
115-h over a predetermined period of time, as observed and stored
by the server, the serving cell, and/or the mobile device
115-h.
[0120] The cell measurement module 925 may be configured to perform
signal strength measurements on the one or more neighboring cells
according to the determinations made by the prediction module 920.
For example, the cell measurement module may make measurements of
an identified subset of the neighboring cells and report the signal
strength measurements to the serving cell. The handover module 930
may be configured to perform a handover or reselection of the
mobile device 115-h to a target cell in the identified subset. In
certain examples, the serving cell may select the target cell from
the identified subset based on the signal strength measurements
provided by the cell measurement module 925. The serving cell may
then indicate the selected target cell to the mobile device 115-h
through WWAN signaling. Additionally or alternatively, the mobile
device 115-h may perform or aid in the selection of the target cell
based on the signal strength measurements for the identified
subset.
[0121] In certain examples, the identified subset may include a
single neighboring cell. In such cases, the cell measurement module
925 may measure a signal strength associated with the single
neighboring cell, and the handover module 930 may perform a
handover (initiated by the mobile device 115-h or the serving cell)
of the mobile device 115-h to the single neighboring cell if the
signal strength of the single neighboring cell is greater than a
threshold level. Accordingly, the prediction module 920 and cell
measurement module 925 may determine not to perform signal strength
measurements of neighboring cells other than the single neighboring
cell when the signal strength of the single neighboring cell is
greater than a threshold level.
[0122] In certain examples, the prediction module 920 may determine
a quality metric for each of the neighboring cells in the set, and
the subset may be selected to include each neighboring cell that
has a quality metric greater than a threshold level. The quality
metric may be based on, for example, the signal strength of each
neighboring cell, a data rate associated with the neighboring cell,
an ability of the neighboring cell to perform offloading to an
alternate radio access technology, a projected amount of time for
which the mobile device 115-h will remain connected to the
neighboring cell, and/or other relevant factors. In certain
examples, known mean and standard deviation values of the signal
strength for the cell may influence the effect of the signal
strength on the quality metric for that cell. In certain examples,
the prediction module 920 or the serving cell may rank the
neighboring cells in the subset according to their respective
quality metrics.
[0123] In certain examples, the prediction module 920 may base the
quality metric of each neighboring cell on a confidence level. The
confidence level for each neighboring cell may indicate a level of
confidence, based on the historical information 919 for the mobile
device 115-h, that the neighboring cell will be the next cell in a
mobility path of the mobile device 115-h. In such examples, the
identified subset of the neighboring cells may include the
neighboring cells having a confidence level greater than a
threshold level.
[0124] In certain examples, the subset of the neighboring cells
identified for measurement may include neighboring cells with a
confidence level greater than a first threshold (35%). Out of the
identified subset, the prediction module 920 and/or serving cell
may determine that one of the neighboring cells in the subset has a
confidence level greater than a second, higher threshold (e.g.,
90%). In that case, the mobile device 115-h may communicate with
the serving cell to perform a blind handover (e.g., a handover
without measurements) to the neighboring cell having the confidence
level higher than the second threshold.
[0125] In certain examples, the prediction module 920 and/or the
serving cell for the mobile device 115-h may exclude one or more of
the neighboring cells from the subset selected for measurements
based at least on a current speed of the mobile device 115-h and a
signal strength of the one or more neighboring cells. For example,
if the mobile device 115-h is traveling along a known path and
momentarily passes through the coverage area of a femtocell while
the subset of the neighboring cells selected for measurement is
identified, the femtocell may be excluded from the subset of
neighboring cells selected for measurement due to the likelihood
that the mobile device 115-h will soon be outside the coverage area
of the femtocell.
[0126] FIG. 10 shows a block diagram of one example of a base
station 105-1, according to one aspect of the principles described
herein. The base station 105-1 may be an example of one or more of
the base stations 105 described above with reference to the
previous Figures. The base station 105-1 may be associated with a
serving cell of one or more of the mobile devices 115 described
above with reference to the previous Figures.
[0127] The base station 105-1 of FIG. 10 may include a processor
910-a, a memory 915-a, a prediction module 920-a, a cell
measurement requesting module 1025, a handover module 930-a, a
wireless wide area network (WWAN) radio 950-a, and a backhaul/core
network interface 1055. Each of these components may be in
communication, directly or indirectly.
[0128] The processor 910-a may be configured to execute
computer-readable program code stored by the memory 915-a to
implement one or more aspects of the prediction module 920-a, the
cell measurement requesting module 1025, the handover module 930-a,
the WWAN radio 950-a, and/or the backhaul/core network interface
1055. The processor 910-a may also execute computer-readable
program code stored by the memory 915-a to implement other
applications 917-a.
[0129] The prediction module 920-a may be configured to identify a
subset of a set of neighboring cells for measurement by a mobile
device (e.g., one or more of the mobile devices 115 described in
the present disclosure) based on historical information 919-a
associated with mobility patterns of the mobile device. The subset
may further be identified based on a current location or state of
the mobile device in relation to the historical information 919. In
certain examples, the base station 105-1 may select the subset of
the neighboring cells based on the historical information 919-a and
location or state of the mobile device. The base station 105-1 may
then signal (e.g., using the WWAN radio 950-a) the identified
subset of the neighboring cells to the mobile device. Additionally
or alternatively, a separate network entity (e.g., a server or
mobility management entity (MME)) may select the subset of the
neighboring cells based on the historical information 919-a and
location or state of the mobile device and signal (e.g., over the
backhaul/core network interface 1055) the selected subset of the
neighboring cells to the base station 105-1 for forwarding to the
mobile device. In still other examples, the mobile device may
itself select the subset of the neighboring cells based on the
historical information 919-a.
[0130] Additionally or alternatively, the prediction module 920-a
may identify, based on the historical information 919-a, an order
in which measurements of neighboring cells are to be performed
(e.g., according to likelihood of being the next cell) by the
mobile device. In additional or alternative examples, the
prediction module 920-a may identify a frequency with which
measurements of neighboring cells are performed and/or the type of
measurements to take.
[0131] In examples where the base station 105-1 determines the
subset of the neighboring cells to the mobile device for
measurement by the mobile device, the base station 105-1 may
collect and store the historical information 919-a locally in the
memory 915-a of the base station 105-1, as shown in FIG. 10.
[0132] The historical information may include information about the
mobility patterns of the mobile device. The mobility patterns may
include, for example, a route and a schedule of the mobile device
between a first location and a second location. Additionally or
alternatively, the mobility patterns may include a location and a
period of time during which the mobile device remains at the
location. Thus, in certain examples, the historical information may
include a serving cell history of the mobile device over a
predetermined period of time, as collected by a network server, the
base station 105-1, and/or the mobile device 115-f.
[0133] The cell measurement requesting module 1025 may be
configured to instruct the mobile device to perform signal strength
measurements on the one or more neighboring cells in the identified
subset and report the signal strength measurements to the base
station 105-1. The handover module 930-a may be configured to
perform a handover or reselection of the mobile device to a target
cell in the identified subset. In certain examples, the handover
module 930-a of the base station 105-1 may select the target cell
from the identified subset based on the signal strength
measurements at the mobile device provided in response to the
request made by the cell measurement requesting module 1025. The
handover module 930-a of the base station 105-1 may indicate the
selected target cell to the mobile device through WWAN signaling.
Additionally or alternatively, the mobile device may perform or aid
in the selection of the target cell based on the signal strength
measurements for the identified subset.
[0134] In certain examples, the identified subset may include a
single neighboring cell. In such cases, the cell measurement
requesting module 1025 may request signal strength measurements for
the single neighboring cell, and the handover module 930-a may
perform a handover (initiated by the mobile device or the base
station) of the mobile device to the single neighboring cell if the
signal strength of the single neighboring cell is greater than a
threshold level. Accordingly, the prediction module 920-a and cell
measurement requesting module 1025 may determine not to request
signal strength measurements of neighboring cells other than the
single neighboring cell when the signal strength of the single
neighboring cell is greater than a threshold level.
[0135] In certain examples, the prediction module 920-a may
determine a quality metric for each of the neighboring cells in the
set, and the subset may be selected to include each neighboring
cell that has a quality metric greater than a threshold level. The
quality metric may be based on, for example, the signal strength of
each neighboring cell, a data rate associated with the neighboring
cell, an ability of the neighboring cell to perform offloading to
an alternate radio access technology, a projected amount of time
for which the mobile device will remain connected to the
neighboring cell, and/or other relevant factors. In certain
examples, the prediction module 920-a or the serving cell may rank
the neighboring cells in the subset according to their respective
quality metrics.
[0136] In certain examples, the prediction module 920-a may base
the quality metric of each neighboring cell on a confidence level.
The confidence level for each neighboring cell may indicate a level
of confidence, based on the historical information 919-a for the
mobile device, that the neighboring cell will be the next cell in a
mobility path of the mobile device. In such examples, the
identified subset of the neighboring cells may include the
neighboring cells having a confidence level greater than a
threshold level.
[0137] In certain examples, the subset of the neighboring cells
identified for measurement may include neighboring cells with a
confidence level greater than a first threshold (35%). Out of the
identified subset, the prediction module 920-a and/or mobile device
may determine that one of the neighboring cells in the subset has a
confidence level greater than a second, higher threshold (e.g.,
100%). In that case, the base station 105-1 may communicate with
the mobile device to perform a blind handover (e.g., a handover
without measurements) to the neighboring cell having the confidence
level higher than the second threshold.
[0138] In certain examples, the prediction module 920-a and/or the
mobile device may exclude one or more of the neighboring cells from
the subset selected for measurements based at least on a current
speed of the mobile device and a signal strength of the one or more
neighboring cells. For example, if the mobile device is traveling
along a path and momentarily passes through the coverage area of a
femtocell while the subset of the neighboring cells selected for
measurement is identified, the femtocell may be excluded from the
subset of neighboring cells selected for measurement due to the
likelihood that the mobile device will soon be outside the coverage
area of the femtocell.
[0139] FIG. 11 shows a flowchart diagram of a method 1100 for
managing wireless communications, in accordance with an aspect of
the present disclosure. Specifically, FIG. 11 illustrates a method
1100 of improving network and/or mobile device performance based on
learning and predicting the behavior of a mobile device. The method
1100 may be implemented in one or more of the wireless
communications systems 100, 200, 300, 400, 500, 600, 700, 800
described above with respect to the previous Figures. In
particular, the method 1100 may be performed by one or more of the
base stations 105, mobile devices 115, or other nodes described
above with reference to the previous Figures.
[0140] At block 1105, historical information associated with
mobility patterns of a mobile device may be received. The
historical information may be received by collecting and storing
the historical information and/or by receiving the historical
information from another device. At block 1110, a subset of
neighboring cells of the mobile device may be identified for
measurement by the mobile device. The subset of neighboring cells
may be identified for measurement based on the historical
information. Additionally or alternatively, the historical
information may be used to identify or determine an order in which
measurements of neighboring cells are to be performed (e.g.,
according to likelihood of being the next cell), a frequency with
which measurements of neighboring cells are performed, and/or the
type of measurements to take.
[0141] FIG. 12 shows a flowchart diagram of a method 1200 for
managing wireless communications, in accordance with an aspect of
the present disclosure. Specifically, FIG. 12 illustrates a method
1200 of improving network and/or mobile device performance based on
learning and predicting the behavior of a mobile device. The method
1200 may be implemented in one or more of the wireless
communications systems 100, 200, 300, 400, 500, 600, 700, 800
described above with respect to the previous Figures. In
particular, the method 1200 may be performed by one or more of the
base stations 105 or other network devices described above with
reference to the previous Figures.
[0142] At block 1205, historical information associated with
mobility patterns of a mobile device may be received from a server.
The historical information may include a serving cell history for
the mobile device. At block 1210, a set of neighboring cells for
the mobile device may be identified. The set of neighboring cells
may be identified based on a location of the mobile device and/or a
neighboring cell list maintained by the mobile device and/or the
current serving cell of the mobile device.
[0143] At block 1215, a confidence level may be determined for each
of the neighboring cells of the mobile device. The confidence level
of each neighboring cell may indicate a likelihood that that
neighboring cell will be the next cell in a current mobility path
of the mobile device. At block 1220, a subset of the neighboring
cells of the mobile device having a confidence level greater than a
threshold level may be identified. At block 1225, the mobile device
may be instructed to measure the signal strength of the subset of
the neighboring cells. At block 1230, a handover target for the
mobile device may be selected based on the measured signal
strengths. In additional or alternative embodiments, all of the
actions of blocks 1205 through 1230 may be performed by the mobile
device (e.g., when the mobile device is in idle mode). In these
cases, the mobile device may make the decision of the initial cells
to measure based on pre-defined rules and parameters of the
network, taking into account the historical information. In such
embodiments the mobile device may select a reselection target
instead of a handover target at block 1230.
[0144] FIG. 13 shows a flowchart diagram of a method 1300 for
managing wireless communications, in accordance with an aspect of
the present disclosure. Specifically, FIG. 13 illustrates a method
1300 of improving network and/or mobile device performance based on
learning and predicting the behavior of a mobile device. The method
1300 may be implemented in one or more of the wireless
communications systems 100, 200, 300, 400, 500, 600, 700, 800
described above with respect to the previous Figures. In
particular, the method 1300 may be performed by one or more of the
mobile devices 115 or other network devices described above with
reference to the previous Figures.
[0145] At block 1305, a serving cell signal strength, measured at a
mobile device, may be reported to the serving cell. At block 1310,
an instruction may be received from the serving cell to measure the
signal strength of a subset of neighboring cells of the mobile
device. The subset may be identified by the serving cell or the
mobile device based on historical information associated with
mobility patterns of the mobile device. The historical information
may include a serving cell history for the mobile device. At block
1315, signal strength measurements for the identified subset of the
neighboring cells may be transmitted to the serving cell. At block
1320, a handover for the mobile device may be performed with a
target cell selected from the subset of the neighboring cells based
on the signal strength measurements.
[0146] FIG. 14 shows a flowchart diagram of a method 1400 for
managing wireless communications, in accordance with an aspect of
the present disclosure. Specifically, FIG. 14 illustrates a method
1400 of improving network and/or mobile device performance based on
learning and predicting the behavior of a mobile device. The method
1400 may be implemented in one or more of the wireless
communications systems 100, 200, 300, 400, 500, 600, 700, 800
described above with respect to the previous Figures. In
particular, the method 1400 may be performed by one or more of the
mobile devices 115 or other network devices described above with
reference to the previous Figures.
[0147] At block 1405, a mobile device in connected mode may report
a serving cell signal strength to the serving cell. At block 1410,
the mobile device may receive an instruction from the serving cell
to measure the signal strength of all neighboring cells. At block
1415, the mobile device may identify a subset of the neighboring
cells based on historical information associated with mobility
patterns of the mobile device. The historical information may
include a serving cell history for the mobile device. At block
1420, signal strength measurements for only the identified subset
of the neighboring cells may be transmitted to the serving cell
from the mobile device. At block 1425, a handover target may be
selected for the mobile device based on the measured signal
strengths.
[0148] FIG. 15 shows a flowchart diagram of a method 1500 for
managing wireless communications, in accordance with an aspect of
the present disclosure. Specifically, FIG. 15 illustrates a method
1500 of improving network and/or mobile device performance based on
learning and predicting the behavior of a mobile device. The method
1500 may be implemented in one or more of the wireless
communications systems 100, 200, 300, 400, 500, 600, 700, 800
described above with respect to the previous Figures. In
particular, the method 1500 may be performed by one or more of the
mobile devices 115 or other network devices described above with
reference to the previous Figures.
[0149] At block 1505, a mobile device in idle mode may receive an
instruction from a serving cell to measure the signal strength of
all neighboring cells. This instruction may be received as a
broadcast message in one or more system information blocks from the
serving cell. At block 1510, the mobile device may identify a
subset of the neighboring cells based on historical information
associated with mobility patterns of the mobile device. The
historical information may include a serving cell history for the
mobile device. At block 1515, the mobile device may perform signal
strength measurements for the subset of the neighboring cells. At
block 1520, a cell reselection target may be selected for the
mobile device from the subset based on the measured signal
strengths.
[0150] FIG. 16 shows a flowchart diagram of a method 1600 for
managing wireless communications, in accordance with an aspect of
the present disclosure. Specifically, FIG. 16 illustrates a method
1600 of improving network and/or mobile device performance based on
learning and predicting the behavior of a mobile device. The method
1600 may be implemented in one or more of the wireless
communications systems 100, 200, 300, 400, 500, 600, 700, 800
described above with respect to the previous Figures. In
particular, the method 1600 may be performed by one or more of the
mobile devices 115 or other network devices described above with
reference to the previous Figures.
[0151] At block 1605, the mobile device may report to a serving
cell a signal strength measurement of the serving cell. The signal
strength of the serving cell may indicate an imminent handover of
the mobile device. At block 1610, a subset of neighboring cells of
the mobile device may be identified for measurement by the mobile
device based on historical information associated with mobility
patterns of the mobile device. The historical information may
include a serving cell history for the mobile device. The target
handover cell may be identified based on a determination that a
confidence level of the target handover cell is greater than a
threshold level. At block 1615, the mobile device may communicate
with the serving cell to coordinate a blind handover of the mobile
device to the identified target handover cell without performing
signal strength measurements for any of the neighboring cells.
[0152] The detailed description set forth above in connection with
the appended drawings describes exemplary embodiments and does not
represent the only embodiments that may be implemented or that are
within the scope of the claims. The term "exemplary" used
throughout this description means "serving as an example, instance,
or illustration," and not "preferred" or "advantageous over other
embodiments." The detailed description includes specific details
for the purpose of providing an understanding of the described
techniques. These techniques, however, may be practiced without
these specific details. In some instances, well-known structures
and devices are shown in block diagram form in order to avoid
obscuring the concepts of the described embodiments.
[0153] Information and signals may be represented using any of a
variety of different technologies and techniques. For example,
data, instructions, commands, information, signals, bits, symbols,
and chips that may be referenced throughout the above description
may be represented by voltages, currents, electromagnetic waves,
magnetic fields or particles, optical fields or particles, or any
combination thereof.
[0154] The various illustrative blocks and modules described in
connection with the disclosure herein may be implemented or
performed with a general-purpose processor, a digital signal
processor (DSP), an application specific integrated circuit (ASIC),
a field programmable gate array (FPGA) or other programmable logic
device, discrete gate or transistor logic, discrete hardware
components, or any combination thereof designed to perform the
functions described herein. A general-purpose processor may be a
microprocessor, but in the alternative, the processor may be any
conventional processor, controller, microcontroller, or state
machine. A processor may also be implemented as a combination of
computing devices, e.g., a combination of a DSP and a
microprocessor, multiple microprocessors, one or more
microprocessors in conjunction with a DSP core, or any other such
configuration.
[0155] The functions described herein may be implemented in
hardware, software executed by a processor, firmware, or any
combination thereof. If implemented in software executed by a
processor, the functions may be stored on or transmitted over as
one or more instructions or code on a computer-readable medium.
Other examples and implementations are within the scope and spirit
of the disclosure and appended claims. For example, due to the
nature of software, functions described above can be implemented
using software executed by a processor, hardware, firmware,
hardwiring, or combinations of any of these. Features implementing
functions may also be physically located at various positions,
including being distributed such that portions of functions are
implemented at different physical locations. Also, as used herein,
including in the claims, "or" as used in a list of items prefaced
by "at least one of" indicates a disjunctive list such that, for
example, a list of "at least one of A, B, or C" means A or B or C
or AB or AC or BC or ABC (i.e., A and B and C).
[0156] Computer-readable media includes both computer storage media
and communication media including any medium that facilitates
transfer of a computer program from one place to another. A storage
medium may be any available medium that can be accessed by a
general purpose or special purpose computer. By way of example, and
not limitation, computer-readable media can comprise RAM, ROM,
EEPROM, CD-ROM or other optical disk storage, magnetic disk storage
or other magnetic storage devices, or any other medium that can be
used to carry or store desired program code means in the form of
instructions or data structures and that can be accessed by a
general-purpose or special-purpose computer, or a general-purpose
or special-purpose processor. Also, any connection is properly
termed a computer-readable medium. For example, if the software is
transmitted from a website, server, or other remote source using a
coaxial cable, fiber optic cable, twisted pair, digital subscriber
line (DSL), or wireless technologies such as infrared, radio, and
microwave, then the coaxial cable, fiber optic cable, twisted pair,
DSL, or wireless technologies such as infrared, radio, and
microwave are included in the definition of medium. Disk and disc,
as used herein, include compact disc (CD), laser disc, optical
disc, digital versatile disc (DVD), floppy disk and Blu-Ray disc
where disks usually reproduce data magnetically, while discs
reproduce data optically with lasers. Combinations of the above are
also included within the scope of computer-readable media.
[0157] The previous description of the disclosure is provided to
enable a person skilled in the art to make or use the disclosure.
Various modifications to the disclosure will be readily apparent to
those skilled in the art, and the generic principles defined herein
may be applied to other variations without departing from the
spirit or scope of the disclosure. Throughout this disclosure the
term "example" or "exemplary" indicates an example or instance and
does not imply or require any preference for the noted example.
Thus, the disclosure is not to be limited to the examples and
designs described herein but is to be accorded the widest scope
consistent with the principles and novel features disclosed
herein.
* * * * *