U.S. patent application number 12/884377 was filed with the patent office on 2011-09-15 for system and method for implementing power distribution.
This patent application is currently assigned to FUJITSU LIMITED. Invention is credited to Wei-Peng Chen.
Application Number | 20110223959 12/884377 |
Document ID | / |
Family ID | 44560477 |
Filed Date | 2011-09-15 |
United States Patent
Application |
20110223959 |
Kind Code |
A1 |
Chen; Wei-Peng |
September 15, 2011 |
System and Method for Implementing Power Distribution
Abstract
A method, in accordance with particular embodiments, includes
establishing a plurality of wireless connections with a plurality
of endpoints. The connections are established via one or more of a
plurality of remote transceivers. The method also includes
determining a plurality of candidates for a positive power gain.
The plurality of candidates includes a plurality of unique
pairings, each pairing comprising a combination of one endpoint and
one remote transceiver. The method additional includes identifying
a subset of the plurality of candidates. The method further
includes determining whether the identified subset results in an
optimum power distribution. If the identified subset results in a
less than optimum power distribution, the method includes
identifying a different subset of candidates. If the identified
subset results in an optimum power distribution, the method
includes computing a non-uniform power distribution based on the
identified subset.
Inventors: |
Chen; Wei-Peng; (Fremont,
CA) |
Assignee: |
FUJITSU LIMITED
Kanagawa
JP
|
Family ID: |
44560477 |
Appl. No.: |
12/884377 |
Filed: |
September 17, 2010 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61312415 |
Mar 10, 2010 |
|
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Current U.S.
Class: |
455/522 |
Current CPC
Class: |
H04B 7/15535 20130101;
H04B 7/0615 20130101; H04B 7/0617 20130101; H04W 72/0473 20130101;
H04W 88/085 20130101; H04W 52/143 20130101; H04B 7/022 20130101;
H04W 52/267 20130101; H04W 52/24 20130101; H04W 52/386 20130101;
Y02D 30/70 20200801; H04W 52/241 20130101; H04W 52/20 20130101;
H04W 52/40 20130101 |
Class at
Publication: |
455/522 |
International
Class: |
H04W 52/00 20090101
H04W052/00 |
Claims
1. A method for adjusting power distribution comprising:
establishing a connection between a base station and a plurality of
remote transceivers; establishing a plurality of wireless
connections with a plurality of endpoints via one or more of the
plurality of remote transceivers; determining a signal quality
associated with each endpoint as received at each remote
transceiver; heuristically repeating the following steps until a
potential solution is determined in which any error determined
based on the potential solution is less than a threshold value:
generating a power matrix based on the received signal quality
associated with each endpoint at each remote transceiver, the
generated power matrix differing each time it is generated;
determining the potential solution to a linear equation using the
power matrix; comparing the potential solution to the linear
equation to a pervious solution to the linear equation; upon the
potential solution being an improvement over the previous solution,
determining at least one error value based on the potential
solution; and upon the at least one error value being less than the
threshold value, determining a power distribution for each endpoint
at each remote transceiver based on the potential solution.
2. The method of claim 1, wherein generating the power matrix a
first time comprises: identifying, for each remote transceiver, one
endpoint of the plurality of endpoints having a highest received
power at the respective remote transceiver; identifying, for each
unaccounted endpoint that was not identified as having the highest
received power at any of the remote transceivers, one remote
transceiver of the plurality of remote transceivers for which the
received power from the unaccounted endpoint is highest.
3. The method of claim 2, wherein generating the power matrix each
subsequent time after the first time comprises identifying at least
one additional wireless connection between one of the plurality of
endpoints and one of the plurality of remote transceivers, the at
least one wireless connection having the a highest received power
among wireless connections not associated with the remote
transceivers and endpoints previously identified.
4. The method of claim 3, wherein the received power associated
with the identified at least one additional wireless connection
satisfies an inequality constraint configured to reduce a number of
iterations needed to determine an acceptable potential
solution.
5. The method of claim 1, wherein determining a potential solution
to a linear equation using the power matrix comprises: forming a
square matrix comprising a plurality of rows, each of the plurality
of rows based on a different one of the values of the power matrix;
forming a column matrix comprising a single column of values, each
value based on a different one of the values of the power matrix;
and solving a linear equation based on the square matrix and the
column matrix.
6. The method of claim 5, wherein at least one row of the plurality
of rows of the square matrix comprises at least one value based on
the determined signal quality associated with a first endpoint at a
first remote transceiver.
7. The method of claim 1, wherein determining at least one error
value based on the potential solution comprises applying each of a
plurality of optimality conditions to the potential solution.
8. A method for adjusting power distribution comprising:
establishing a plurality of wireless connections with a plurality
of endpoints via one or more of a plurality of remote transceivers;
determining a plurality of candidates for a positive power gain,
the candidates comprising a plurality of unique pairings, each
pairing comprising a combination of one endpoint and one remote
transceiver; identifying a subset of the plurality of candidates;
determining whether the identified subset results in an optimum
power distribution; if the identified subset results in a less than
optimum power distribution, identifying a different subset of
candidates; and if the identified subset results in an optimum
power distribution, computing a non-uniform power distribution
based on the identified subset.
9. The method of claim 8, further comprising determining a received
power associated with each unique pairing of one endpoint and one
remote transceiver.
10. The method of claim 9, further comprising generating a power
matrix indicative of the determined plurality of candidates, the
determined plurality of candidates based on the received power
associated with each unique pairing of one endpoint and one remote
transceiver.
11. The method of claim 10, wherein generating the power matrix a
first time comprises: identifying, for each remote transceiver, one
endpoint of the plurality of endpoints having a highest received
power at the respective remote transceiver; and identifying, for
each unaccounted endpoint that was not identified as having a
highest received power at any of the remote transceivers, one
remote transceiver of the plurality of remote transceivers for
which the received power from the unaccounted endpoint is
highest.
12. The method of claim 10, further comprising: determining a
potential solution to a linear equation using the power matrix;
comparing the potential solution to the linear equation to a
pervious solution to the linear equation; upon the potential
solution being an improvement over the previous solution,
determining at least one error value based on the potential
solution; and upon the at least one error value being less than a
threshold value, determining a power distribution for each endpoint
at each remote transceiver based on the potential solution.
13. The method of claim 12, wherein determining at least one error
value based on the potential solution comprises applying each of a
plurality of optimality conditions to the potential solution.
14. The method of claim 12, wherein determining a potential
solution to a linear equation using the power matrix comprises:
forming a square matrix comprising a plurality of rows, each of the
plurality of rows based on a different one of the values of the
power matrix; forming a column matrix comprising a single column of
values, each value based on a different one of the values of the
power matrix; and solving a linear equation based on the square
matrix and the column matrix.
15. A system for adjusting power distribution comprising: an
interface configured to establish a plurality of wireless
connections with a plurality of endpoints via one or more of a
plurality of remote transceivers; a processor coupled to the
interface and configured to: determine a plurality of candidates
for a positive power gain, the candidates comprising a plurality of
unique pairings, each pairing comprising a combination of one
endpoint and one remote transceiver; identify a subset of the
plurality of candidates; determine whether the identified subset
results in an optimum power distribution; if the identified subset
results in a less than optimum power distribution, identify a
different subset of candidates; and if the identified subset
results in an optimum power distribution, compute a non-uniform
power distribution based on the identified subset.
16. The system of claim 15, wherein the processor is further
configured to determine a received power associated with each
unique pairing of one endpoint and one remote transceiver.
17. The system of claim 16, wherein the processor is further
configured to generate a power matrix indicative of the determined
plurality of candidates, the determined plurality of candidates
based on the received power associated with each unique pairing of
one endpoint and one remote transceiver.
18. The system of claim 17, wherein the processor configured to
generate the power matrix is further configured to, when generating
the power matrix a first time: identify, for each remote
transceiver, one endpoint of the plurality of endpoints having a
highest received power at the respective remote transceiver; and
identify, for each unaccounted endpoint that was not identified as
having a highest received power at any of the remote transceivers,
one remote transceiver of the plurality of remote transceivers for
which the received power from the unaccounted endpoint is
highest.
19. The system of claim 17, wherein the processor is further
configured to: determine a potential solution to a linear equation
using the power matrix; compare the potential solution to the
linear equation to a pervious solution to the linear equation; upon
the potential solution being an improvement over the previous
solution, determine at least one error value based on the potential
solution; and upon the at least one error value being less than a
threshold value, determine a power distribution for each endpoint
at each remote transceiver based on the potential solution.
20. The system of claim 19, wherein the processor configured to
determine at least one error value based on the potential solution
is further configured to apply each of a plurality of optimality
conditions to the potential solution.
21. The system of claim 19, wherein the processor configured to
determine a potential solution to a linear equation using the power
matrix is further configured to: form a square matrix comprising a
plurality of rows, each of the plurality of rows based on a
different one of the values of the power matrix; form a column
matrix comprising a single column of values, each value based on a
different one of the values of the power matrix; and solve a linear
equation based on the square matrix and the column matrix.
22. One or more computer-readable non-transitory storage media
embodying software that when executed by a processor is operable
to: establish a plurality of wireless connections with a plurality
of endpoints via one or more of a plurality of remote transceivers;
determine a plurality of candidates for a positive power gain, the
candidates comprising a plurality of unique pairings, each pairing
comprising a combination of one endpoint and one remote
transceiver; identify a subset of the plurality of candidates;
determine whether the identified subset results in an optimum power
distribution; if the identified subset results in a less than
optimum power distribution, identify a different subset of
candidates; and if the identified subset results in an optimum
power distribution, compute a non-uniform power distribution based
on the identified subset.
23. The media of claim 22, wherein the software when executed by
the processor is further configured to determine a received power
associated with each unique pairing of one endpoint and one remote
transceiver.
24. The media of claim 23, wherein the software when executed by
the processor is further configured to generate a power matrix
indicative of the determined plurality of candidates, the
determined plurality of candidates based on the received power
associated with each unique pairing of one endpoint and one remote
transceiver.
25. The media of claim 24, wherein the software configured to
generate the power matrix a first time comprises software that when
executed by the processor is configured: identify, for each remote
transceiver, one endpoint of the plurality of endpoints having a
highest received power at the respective remote transceiver; and
identify, for each unaccounted endpoint that was not identified as
having a highest received power at any of the remote transceivers,
one remote transceiver of the plurality of remote transceivers for
which the received power from the unaccounted endpoint is
highest.
26. The media of claim 24, wherein the software when executed by
the processor is further configured to: determine a potential
solution to a linear equation using the power matrix; compare the
potential solution to the linear equation to a pervious solution to
the linear equation; upon the potential solution being an
improvement over the previous solution, determine at least one
error value based on the potential solution; and upon the at least
one error value being less than a threshold value, determine a
power distribution for each endpoint at each remote transceiver
based on the potential solution.
27. The media of claim 26, wherein the software that when executed
by a processor is configured to determine at least one error value
based on the potential solution is further configured to apply each
of a plurality of optimality conditions to the potential
solution.
28. The media of claim 26, wherein the software that when executed
by a processor is configured to determine a potential solution to a
linear equation using the power matrix is further configured to:
form a square matrix comprising a plurality of rows, each of the
plurality of rows based on a different one of the values of the
power matrix; form a column matrix comprising a single column of
values, each value based on a different one of the values of the
power matrix; and solve a linear equation based on the square
matrix and the column matrix.
Description
RELATED APPLICATION
[0001] This application claims the benefit under 35 U.S.C.
.sctn.119(e) of U.S. Provisional Application Ser. No. 61/312,415,
filed Mar. 10, 2010 and entitled "Method and System for Enhancing
Capability of Distributed Antenna System."
TECHNICAL FIELD OF THE INVENTION
[0002] This invention relates in general to wireless networks and,
more particularly, to a system and method for implementing power
distribution.
BACKGROUND OF THE INVENTION
[0003] Distributed antenna systems consist of a base station (also
known as a Radio Element Control or a Baseband Unit) and one or
more remote transceivers (also known as Radio Elements or Remote
Radio Heads). These components provide endpoints with wireless
network access. To aid the distributed antenna system in
distinguishing between the various wireless transmissions to and
from the various endpoints, each endpoint may have one or more
unique subcarriers assigned thereto.
[0004] Within a distributed antenna system, the remote transceivers
are distributed around different geographic locations while being
connected via a wired connection (e.g., optical fiber) to the base
station. Wile there may be multiple remote transceivers, from the
perspective of an endpoint there is only one entity, the base
station. That is, each remote transceiver transmits essentially the
same core data, and the endpoint combines multiple signals from
multiple remote transceivers into a single communication.
[0005] The base station communicates with the remote transceivers
using, for example, the Common Public Radio Interface (CPRI)
standard. The CPRI standard allows in-phase/quadrature (I/Q) data
to be transmitted from the base station to the remote transceivers.
The remote transceivers use the I/Q data to form the transmissions
that are sent to any endpoints connected thereto. The remote
transceivers are also able to communicate with the base station
using the CPRI standard. This allows the remote transceivers to
relay data received from the endpoints and to communicate control
information, such as signal quality, to the base station.
SUMMARY
[0006] In accordance with a particular embodiment, a method
includes establishing a plurality of wireless connections with a
plurality of endpoints. The connections are established via one or
more of a plurality of remote transceivers. The method also
includes determining a plurality of candidates for a positive power
gain. The plurality of candidates includes a plurality of unique
pairings, each pairing comprising a combination of one endpoint and
one remote transceiver. The method additionally includes
identifying a subset of the plurality of candidates. The method
further includes determining whether the identified subset results
in an optimum power distribution. If the identified subset results
in a less than optimum power distribution, the method includes
identifying a different subset of candidates. If the identified
subset results in an optimum power distribution, the method
includes computing a non-uniform power distribution based on the
identified subset.
[0007] Technical advantages of particular embodiments may include
determining an optimal power distribution among remote transceivers
in a computationally quick manner. Another technical advantage of
particular embodiments may include increasing the system capacity
by improving the power distribution within a distributed antenna
system.
[0008] Other technical advantages will be readily apparent to one
skilled in the art from the following figures, descriptions and
claims. Moreover, while specific advantages have been enumerated
above, various embodiments may include all, some or none of the
enumerated advantages.
BRIEF DESCRIPTION OF THE DRAWINGS
[0009] For a more complete understanding of particular embodiments
and their advantages, reference is now made to the following
description, taken in conjunction with the accompanying drawings,
in which:
[0010] FIG. 1 illustrates a distributed antenna system comprising a
base station and a plurality of remote transceivers, in accordance
with a particular embodiment;
[0011] FIG. 2 illustrates a detailed block diagram of a base
station and a remote transceiver within a distributed antenna
system, in accordance with a particular embodiment;
[0012] FIG. 3A illustrates a method for implementing power
distribution within a distributed antenna system, in accordance
with a particular embodiment; and
[0013] FIG. 3B illustrates several sample models to help illustrate
corresponding steps in the method depicted in FIG. 3A, in
accordance with a particular embodiment.
DETAILED DESCRIPTION
[0014] FIG. 1 illustrates a distributed antenna system comprising a
base station and a plurality of remote transceivers, in accordance
with a particular embodiment. Distributed antenna system 100
comprises base station 110 and multiple remote transceivers 120.
Wireless communications may be transmitted by remote transceivers
120 at varying power levels to different endpoints. For example,
more power may be allocated to an endpoint that is closer to a
remote transceiver. This may be based on the notion that the
benefit of increasing the transmission power to a nearby endpoint
is greater than the resulting loss from decreasing the transmission
power to a distant endpoint. The power of a particular
transmission, comprising one or more subcarriers, from a particular
remote transceiver (e.g., remote transceiver 120d) to a particular
endpoint (e.g., endpoint 140c) may depend on the signal quality
between the particular endpoint and the particular remote
transceiver. The transmission power of each subcarrier at each
remote transceiver may be greater than or less than a standard
power level. The standard power level may be based on an equal
distribution of power among the subcarriers (e.g., all
transmissions are transmitted with the same power). Increasing or
decreasing the transmission power for each endpoint 140 at each
remote transceiver 120 may increase the capacity of distributed
antenna system 100 as compared to a system utilizing uniform power
across all subcarriers.
[0015] In certain embodiments, base station 110 may be able to
quickly determine an optimum distribution of power for each
endpoint 140 at each remote transceiver 120. For example, base
station 110 may determine the optimum distribution by solving a
convex optimization problem using an intelligent heuristic
algorithm that is able to be run in polynomial time. The
non-uniform distribution of power to different subcarriers at
different remote transceivers may increase the capacity of
distributed antennas system 100, as compared to a blanket
transmission scheme in a traditional distributed antenna
system.
[0016] Distributed antenna system 100 may be coupled to network 130
via base station 110. Distributed antenna system 100 may provide
wireless coverage for endpoints 140 over a large geographic area.
For example, a single base station (e.g., base station 110) and a
plurality of remote transceivers (e.g., remote transceivers 120)
may be used to provide wireless coverage for an entire building. In
distributed antenna system 100, remote transceivers 120 may differ
from relay stations in that they have a wired connection to base
station 110 as opposed to a wireless connection as used by
traditional relay stations. In some embodiments, remote
transceivers 120 may comprise reduced intelligence compared to
relay stations or base stations. In some embodiments, base station
110 and remote transceivers 120 may together comprise the
functionality of a traditional macro base station, wherein base
station 110 comprises the logic to manage the wireless connections
with endpoints 140 (e.g., assign channels and power levels) and
remote transceivers 120 may comprise the components for
communicating with the endpoints (e.g., radios, analog-to-digital
and digital-to-analog converters). Distributed antenna system 100
may reduce the operational and deployment cost by reducing the
radiated power (e.g., spreading remote transceivers 120 over a wide
area eliminates the need for a powerful central transceiver to
cover the same wide area) and providing deployment flexibility
(e.g., remote transceivers 120 may be small in size compared to
other types of relay stations, repeaters or macro base
stations).
[0017] In some embodiments, remote transceivers 120 may be part of
a long term deployment plan. For example, when a wireless service
provided first brings wireless service to a new area, it may begin
by deploying a few macro base stations. Each macro base station may
comprise all the features and capabilities needed to provide
wireless service within its associated coverage area. When the
service provider begins to grow the coverage area, fill in gaps in
its coverage area, or respond to increased demand within its
coverage area, the service provider may convert one or more of the
macro base stations into distributed antenna base stations (e.g.,
base station 110) and add one or more remote transceivers. The
conversion may comprise adding a new module to the macro base
station. The wireless service provider may then add additional
remote transceivers as needed. Eventually, the wireless service
provider may decide to convert the remote transceivers to pico base
stations. This may be done by simply adding a module to the remote
transceivers and converting the backhaul connections of remote
transceivers from CPRI connections to IP connections. This upgrade
approach allows a service provide to grow their network in an
incremental approach. This may reduce the cost for the wireless
service provider and provides greater deployment flexibility
compared to traditional deployment techniques of simply adding more
macro or pico base stations.
[0018] Because remote transceivers 120 are distributed over a
geographical area, the distance between an endpoint and each remote
transceiver 120 may be different. In particular embodiments, the
signal quality between an endpoint and a remote transceiver may
generally increase as the endpoint gets closer to the remote
transceiver. Particular embodiments may take advantage of this
increased signal quality by increasing the transmission power for
the subcarriers associated with the signal having the better
quality. Because a remote transceiver has a finite amount of
transmission power, an increase in power for a particular
subcarrier may be balanced by a corresponding decrease in power of
another subcarrier. One possible way in which base station 110 may
estimate how close an endpoint is to one or more of remote
transceivers 120 is to estimate the dominant part of a channel
response (e.g., slow fading) associated with the endpoint.
[0019] Depending on the embodiment, distributed antenna system 100
may use any of a variety of wireless technologies or protocols
(e.g., IEEE 802.16m or 802.16e, or long term evolution (LTE)) for
communications between remote transceivers 120 and endpoints 140.
The multiple remote transceivers 120 appear to endpoints 140 as a
single entity--an extension of base station 110. Thus, each remote
transceiver 120 may attempt to send the same core data to endpoints
140 and may potentially receive the same data from endpoints 140.
The differences in the data that is sent or received may be the
result of the respective distances of each remote transceiver 120
from a particular endpoint and, as will be discussed in more detail
below, the amount of power applied to each subcarrier at each
remote transceiver.
[0020] Depending on the embodiment, distributed antenna system 100
may use any of a variety of different wired technologies or
protocols (e.g., CPRI) for communications between remote
transceivers 120 and base station 110. In particular embodiments,
base station 110 may be configured to adjust the power, either
directly (e.g., by incorporating the power distribution in the I/Q
samples that are sent to the remote transceivers) or indirectly
(e.g., by providing power distribution values to each remote
transceiver from which the remote transceivers can determine their
respective power distribution), that each remote transceiver
applies to its transmissions. By selectively increasing or
decreasing the transmission power for particular sub-carriers
(associated with particular endpoints) at particular remote
transceivers, base station 110 may be able to more efficiently use
the available wireless resources.
[0021] Depending on the embodiment, base station 110 may use signal
quality information from the various remote transceivers to
determine the power distribution for each sub-carrier for each
remote transceiver 120. The signal quality information may include
the received uplink power strength, the maximal usable modulation
and coding scheme (MCS) level, the carrier to
interference-plus-noise ratio (CINR) of the wireless connection,
and/or the signal to interference plus noise ratio (SINR) of the
wireless connection. In particular embodiments, uplink sounding may
be used to estimate the channel gain and interference strength
between endpoints 140 and remote transceivers 120.
[0022] Network 130 may be any network or combination of networks
capable of transmitting signals, data, and/or messages, including
signals, data or messages transmitted through WebPages, e-mail,
text chat, voice over IP (VoIP), and instant messaging. Network 130
may include one or more LANs, WANs, MANs, PSTNs, WiMAX networks,
global distributed networks such as the Internet, Intranet,
Extranet, or any other form of wireless or wired networking.
Network 130 may use any of a variety of protocols for either wired
or wireless communication.
[0023] Base station 110 may include any combination of hardware,
software embedded in a computer readable medium, and/or encoded
logic incorporated in hardware or otherwise stored (e.g., firmware)
to implement any number of communication protocols that allow for
the wireless exchange of packets in distributed antenna system 100.
Base station 110 may be configured to determine and distribute a
power distribution to each remote transceiver 120. Depending on the
embodiment, base station 110 may apply the power distribution to
the data before it is sent to the remote transceivers for
transmission or base station 110 may allow each remote transceivers
120 to individually apply the power distribution.
[0024] Remote transceivers 120 may include any combination of
hardware, software embedded in a computer readable medium, and/or
encoded logic incorporated in hardware or otherwise stored (e.g.,
firmware) to implement any number of communication protocols that
allow for the wireless exchange of packets with endpoints 140 in
distributed antenna system 100. In some embodiments, remote
transceivers 120 receive data from base station 110 that may
already include the power distribution determinations made by base
station 110. In particular embodiments, each remote transceiver 120
may adjust the transmission power of the core data received from
base station 110. The adjustments may be made based on one or more
control signals sent from base station 110 specifying the
transmission power for each sub-carrier, or plurality of
sub-carriers, at each respective remote transceiver 120.
[0025] Endpoints 140 may comprise any type of wireless device able
to send and receive data and/or signals to and from base station
110 via remote transceivers 120. Some possible types of endpoints
140 may include desktop computers, PDAs, cell phones, laptops,
and/or VoIP phones. Endpoints 140 may provide data or network
services to a user through any combination of hardware, software
embedded in a computer readable medium, and/or encoded logic
incorporated in hardware or otherwise stored (e.g., firmware).
Endpoints 140 may also include unattended or automated systems,
gateways, other intermediate components or other devices that can
send or receive data and/or signals.
[0026] The following example may help illustrate particular
features of certain embodiments. For purposes of this example,
assume that base station 110 only controls two remote transceivers,
remote transceivers 120a and 120d. Further assume that endpoints
140c and 140e are both located in the area served by remote
transceivers 120a and 120d. To simplify the scenario, assume that
the scheduling algorithm at base station 110 allocates the same
number of subcarriers in a frame to each of endpoints 140c and
140e. Further assume that the magnitude of the channel gain between
remote transceiver 120a and endpoint 140c is twice that of remote
transceiver 120a and endpoint 140e; and that the magnitude of the
channel gain between remote transceiver 120d and endpoint 140e is
twice that of remote transceiver 120d and endpoint 140c. Based on
these assumptions, base station 110 may allocate 2/3 of remote
transceiver 120a's power to the subcarriers used by endpoint 140c
and 1/3 to the subcarriers used by endpoint 140e (as opposed to the
even 1/2 and 1/2 distribution of a standard distributed antenna
system). Similarly, base station 110 may allocate 2/3 of remote
transceiver 120d's power to the subcarriers used by endpoint 140e
and 1/3 to the subcarriers used by endpoint 140c.
[0027] Although FIG. 1 illustrates a particular number and
configuration of endpoints, connections, links, and nodes,
distributed antenna system 100 contemplates any number or
arrangement of such components for communicating data. In addition,
elements of distributed antenna system 100 may include components
centrally located (local) with respect to one another or
distributed throughout distributed antenna system 100.
[0028] FIG. 2 illustrates a detailed block diagram of a base
station and a remote transceiver within a distributed antenna
system, in accordance with a particular embodiment. Distributed
antenna system 200 may be used with any of a variety of different
wireless technologies, including, but not limited to, orthogonal
frequency division multiple access (OFDMA), next generation
wireless system such as LTE-A and 802.16m.
[0029] Distributed antenna system 200 includes base station 210 and
remote transceivers 220. Base station 210 and remote transceivers
220 may each include one or more portions of one or more computer
systems. In particular embodiments, one or more of these computer
systems may perform one or more steps of one or more methods
described or illustrated herein. In particular embodiments, one or
more computer systems may provide functionality described or
illustrated herein. In particular embodiments, encoded software
running on one or more computer systems may perform one or more
steps of one or more methods described or illustrated herein or
provide functionality described or illustrated herein.
[0030] The components of base station 210 and remote transceiver
220 may comprise any suitable physical form, configuration, number,
type and/or layout. As an example, and not by way of limitation,
base station 210 and/or remote transceiver 220 may comprise an
embedded computer system, a system-on-chip (SOC), a single-board
computer system (SBC) (such as, for example, a computer-on-module
(COM) or system-on-module (SOM)), a desktop computer system, a
laptop or notebook computer system, an interactive kiosk, a
mainframe, a mesh of computer systems, a mobile telephone, a
personal digital assistant (PDA), a server, or a combination of two
or more of these. Where appropriate, base station 210 and/or remote
transceiver 220 may include one or more computer systems; be
unitary or distributed; span multiple locations; span multiple
machines; or reside in a cloud, which may include one or more cloud
components in one or more networks.
[0031] Where appropriate, distributed antenna system 200 may
perform without substantial spatial or temporal limitation one or
more steps of one or more methods described or illustrated herein.
As an example, and not by way of limitation, distributed antenna
system 200 may perform in real time or in batch mode one or more
steps of one or more methods described or illustrated herein. One
or more distributed antenna systems may perform at different times
or at different locations one or more steps of one or more methods
described or illustrated herein, where appropriate.
[0032] In the depicted embodiment, base station 210 and remote
transceiver 220 each include their own respective processors 211
and 221, memory 213 and 223, storage 215 and 225, interfaces 217
and 227, and buses 212 and 222. These components may work together
to provide a distributed antenna system in which the power
distribution for each endpoint at each remote transceiver 220 is
distributed based on a relative signal quality for each endpoint at
each remote transceiver. Although a particular distributed antenna
system is depicted having a particular number of particular
components in a particular arrangement, this disclosure
contemplates any suitable distributed antenna system 200 having any
suitable number of any suitable components in any suitable
arrangement. For simplicity, similar components of base station 210
and remote transceiver 220 will be discussed together wherein the
components of remote transceiver 220 will be identified in
parenthesis. However, it is not necessary for both devices to have
the same components, or the same type of components. For example,
processor 211 may be a general purpose microprocessor and processor
221 may be an application specific integrated circuit (ASIC).
[0033] Processor 211 (and/or 221) may be a microprocessor,
controller, or any other suitable computing device, resource, or
combination of hardware, software and/or encoded logic operable to
provide, either alone or in conjunction with other components,
(e.g., memory 213 or 223, respectively) wireless networking
functionality. Such functionality may include providing various
wireless features discussed herein. For example, processor 211 may
determine how to allocate power for each sub-carrier at each remote
transceiver 220. Additional examples and functionality provided, at
least in part, by processor 211 (and/or 221) will be discussed
below.
[0034] In particular embodiments, processor 211 (and/or 221) may
include hardware for executing instructions, such as those making
up a computer program. As an example and not by way of limitation,
to execute instructions, processor 211 (and/or 221) may retrieve
(or fetch) instructions from an internal register, an internal
cache, memory 213 (and/or 223), or storage 215 (and/or 225); decode
and execute them; and then write one or more results to an internal
register, an internal cache, memory 213 (and/or 223), or storage
215 (and/or 225).
[0035] In particular embodiments, processor 211 (and/or 221) may
include one or more internal caches for data, instructions, or
addresses. This disclosure contemplates processor 211 (and/or 221)
including any suitable number of any suitable internal caches,
where appropriate. As an example and not by way of limitation,
processor 211 (and/or 221) may include one or more instruction
caches, one or more data caches, and one or more translation
lookaside buffers (TLBs). Instructions in the instruction caches
may be copies of instructions in memory 213 (and/or 223) or storage
215 (and/or 225) and the instruction caches may speed up retrieval
of those instructions by processor 211 (and/or 221). Data in the
data caches may be copies of data in memory 213 (and/or 223) or
storage 215 (and/or 225) for instructions executing at processor
211 (and/or 221) to operate on; the results of previous
instructions executed at processor 211 (and/or 221) for access by
subsequent instructions executing at processor 211 (and/or 221), or
for writing to memory 213 (and/or 223), or storage 215 (and/or
225); or other suitable data. The data caches may speed up read or
write operations by processor 211 (and/or 221). The TLBs may speed
up virtual-address translations for processor 211 (and/or 221). In
particular embodiments, processor 211 (and/or 221) may include one
or more internal registers for data, instructions, or addresses.
Depending on the embodiment, processor 211 (and/or 221) may include
any suitable number of any suitable internal registers, where
appropriate. Where appropriate, processor 211 (and/or 221) may
include one or more arithmetic logic units (ALUs); be a multi-core
processor; include one or more processors 211 (and/or 221); or any
other suitable processor.
[0036] Memory 213 (and/or 223) may be any form of volatile or
non-volatile memory including, without limitation, magnetic media,
optical media, random access memory (RAM), read-only memory (ROM),
flash memory, removable media, or any other suitable local or
remote memory component or components. Memory 213 (and/or 223) may
store any suitable data or information utilized by base station 210
(and/or remote transceiver 220), including software embedded in a
computer readable medium, and/or encoded logic incorporated in
hardware or otherwise stored (e.g., firmware). In particular
embodiments, memory 213 (and/or 223) may include main memory for
storing instructions for processor 211 (and/or 221) to execute or
data for processor 211 (and/or 221) to operate on. As an example
and not by way of limitation, base station 210 may load
instructions from storage 215 (and/or 225) or another source (such
as, for example, another computer system, another base station, or
a remote transceiver) to memory 213 (and/or 223). Processor 211
(and/or 221) may then load the instructions from memory 213 (and/or
223) to an internal register or internal cache. To execute the
instructions, processor 211 (and/or 221) may retrieve the
instructions from the internal register or internal cache and
decode them. During or after execution of the instructions,
processor 211 (and/or 221) may write one or more results (which may
be intermediate or final results) to the internal register or
internal cache. Processor 211 (and/or 221) may then write one or
more of those results to memory 213 (and/or 223). In particular
embodiments, processor 211 (and/or 221) may execute only
instructions in one or more internal registers or internal caches
or in memory 213 (and/or 223) (as opposed to storage 215 (and/or
225) or elsewhere) and may operate only on data in one or more
internal registers or internal caches or in memory 213 (and/or 223)
(as opposed to storage 215 (and/or 225) or elsewhere).
[0037] Bus 212 (and/or 222) may include any combination of
hardware, software embedded in a computer readable medium, and/or
encoded logic incorporated in hardware or otherwise stored (e.g.,
firmware) to couple components of base station 210 (and/or remote
transceiver 220) to each other. As an example and not by way of
limitation, bus 212 (and/or 222) may include an Accelerated
Graphics Port (AGP) or other graphics bus, an Enhanced Industry
Standard Architecture (EISA) bus, a front-side bus (FSB), a
HYPERTRANSPORT (HT) interconnect, an Industry Standard Architecture
(ISA) bus, an INFINIBAND interconnect, a low-pin-count (LPC) bus, a
memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral
Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a
serial advanced technology attachment (SATA) bus, a Video
Electronics Standards Association local (VLB) bus, or any other
suitable bus or a combination of two or more of these. Bus 212
(and/or 222) may include any number, type, and/or configuration of
buses 212 (and/or 222), where appropriate. In particular
embodiments, one or more buses 212 (which may each include an
address bus and a data bus) may couple processor 211 (and/or 221)
to memory 213 (and/or 223). Bus 212 (and/or 222) may include one or
more memory buses, as described below. In particular embodiments,
one or more memory management units (MMUs) may reside between
processor 211 (and/or 221) and memory 213 (and/or 223) and
facilitate accesses to memory 213 (and/or 223) requested by
processor 211 (and/or 221). In particular embodiments, memory 213
(and/or 223) may include random access memory (RAM). This RAM may
be volatile memory, where appropriate. Where appropriate, this RAM
may be dynamic RAM (DRAM) or static RAM (SRAM). Moreover, where
appropriate, this RAM may be single-ported or multi-ported RAM, or
any other suitable type of RAM or memory. Memory 213 (and/or 223)
may include one or more memories 213 (and/or 223), where
appropriate.
[0038] In particular embodiments, storage 215 (and/or 225) may
include mass storage for data or instructions. As an example and
not by way of limitation, storage 215 (and/or 225) may include an
HDD, a floppy disk drive, flash memory, an optical disc, a
magneto-optical disc, magnetic tape, or a Universal Serial Bus
(USB) drive or a combination of two or more of these. Storage 215
(and/or 225) may include removable or non-removable (or fixed)
media, where appropriate. Storage 215 (and/or 225) may be internal
or external to base station 210 (and/or remote transceiver 220),
where appropriate. In particular embodiments, storage 215 (and/or
225) may be non-volatile, solid-state memory. In particular
embodiments, storage 215 (and/or 225) may include read-only memory
(ROM). Where appropriate, this ROM may be mask-programmed ROM,
programmable ROM (PROM), erasable PROM (EPROM), electrically
erasable PROM (EEPROM), electrically alterable ROM (EAROM), or
flash memory or a combination of two or more of these. Storage 215
(and/or 225) may take any suitable physical form and may comprise
any suitable number or type of storage. Storage 215 (and/or 225)
may include one or more storage control units facilitating
communication between processor 211 (and/or 221) and storage 215
(and/or 225), where appropriate.
[0039] In particular embodiments, interface 217 (and/or 227) may
include hardware, encoded software, or both providing one or more
interfaces for communication (such as, for example, packet-based
communication) between base station 210, remote transceivers 220,
any endpoints (not depicted) being serviced by base station 210,
any networks, any network devices, and/or any other computer
systems. As an example and not by way of limitation, communication
interface 217 (and/or 227) may include a network interface
controller (NIC) or network adapter for communicating with an
Ethernet or other wire-based network and/or a wireless NIC (WNIC)
or wireless adapter for communicating with a wireless network.
[0040] In some embodiments, interface 217 (and/or 227) may comprise
one or more radios coupled to one or more antennas. In such
embodiments, interface 217 (and/or 227) may receive digital data
that is to be sent out to wireless devices, such as endpoints, via
a wireless connection. The radio may convert the digital data into
a radio signal having the appropriate center frequency, bandwidth
parameters, and transmission power. The power distribution for the
radio signal may have been determined and applied to each
subcarrier at base station 210, or the power distribution may be
determined at base station 210 and applied by remote transceivers
220. Similarly, the radios may convert radio signals received via
the antenna into digital data to be processed by, for example,
processor 211 (and/or 221). In some embodiments, base station 210
may process the data by, for example: Determining the received
power from each endpoint at each remote transceiver 220; generating
a power matrix comprising 1's and 0's based on the received power;
solving linear equations based on the power matrix; comparing the
result of the solution to a previous result; if the result (e.g.,
the value of the objective function) is an improvement checking if
the solution of the linear equations provides an acceptable
solution to the Karuch-Kuhn-Tucker (KKT) optimality conditions; if
the if the solution of the linear equations provides an acceptable
solution, determining the power distribution based on the solution
of the linear equations; and if the result is not an improvement or
the solution of the linear equations does not provide an acceptable
solution to the KKT conditions, generating a new power matrix based
on the received power.
[0041] Depending on the embodiment, interface 217 (and/or 227) may
be any type of interface suitable for any type of network for which
distributed antenna system 200 is used. As an example and not by
way of limitation, distributed antenna system 200 may communicate
with an ad-hoc network, a personal area network (PAN), a local area
network (LAN), a wide area network (WAN), a metropolitan area
network (MAN), or one or more portions of the Internet or a
combination of two or more of these. One or more portions of one or
more of these networks may be wired or wireless. As an example,
distributed antenna system 200 may communicate with a wireless PAN
(WPAN) (such as, for example, a BLUETOOTH WPAN), an OFDM network, a
WI-FI network, a WI-MAX network, an LTE network, an LTE-A network,
a cellular telephone network (such as, for example, a Global System
for Mobile Communications (GSM) network), or any other suitable
wireless network or a combination of two or more of these. Base
station 210 (and/or remote transceivers 220) may include any
suitable interface 217 (and/or 227) for any one or more of these
networks, where appropriate.
[0042] In some embodiments, interface 217 (and/or 227) may include
one or more interfaces for one or more I/O devices. One or more of
these I/O devices may enable communication between a person and
base station 210 (and/or remote transceivers 220). As an example
and not by way of limitation, an I/O device may include a keyboard,
keypad, microphone, monitor, mouse, printer, scanner, speaker,
still camera, stylus, tablet, touchscreen, trackball, video camera,
another suitable I/O device or a combination of two or more of
these. An I/O device may include one or more sensors. Particular
embodiments may include any suitable type and/or number of I/O
devices and any suitable type and/or number of interfaces 117
(and/or 227) for them. Where appropriate, interface 117 (and/or
227) may include one or more device or encoded software drivers
enabling processor 211 (and/or 221) to drive one or more of these
I/O devices. Interface 117 (and/or 227) may include one or more
interfaces 117 (and/or 227), where appropriate.
[0043] Herein, reference to a computer-readable storage medium
encompasses one or more tangible computer-readable storage media
possessing structures. As an example and not by way of limitation,
a computer-readable storage medium may include a
semiconductor-based or other integrated circuit (IC) (such, as for
example, a field-programmable gate array (FPGA) or an
application-specific IC (ASIC)), a hard disk, an HDD, a hybrid hard
drive (HHD), an optical disc, an optical disc drive (ODD), a
magneto-optical disc, a magneto-optical drive, a floppy disk, a
floppy disk drive (FDD), magnetic tape, a holographic storage
medium, a solid-state drive (SSD), a RAM-drive, a SECURE DIGITAL
card, a SECURE DIGITAL drive, a flash memory card, a flash memory
drive, or any other suitable computer-readable storage medium or a
combination of two or more of these, where appropriate. Herein,
reference to a computer-readable storage medium excludes any medium
that is not eligible for patent protection under 35 U.S.C.
.sctn.101. Herein, reference to a computer-readable storage medium
excludes transitory forms of signal transmission (such as a
propagating electrical or electromagnetic signal per se) to the
extent that they are not eligible for patent protection under 35
U.S.C. .sctn.101.
[0044] Particular embodiments may include one or more
computer-readable storage media implementing any suitable storage.
In particular embodiments, a computer-readable storage medium
implements one or more portions of processor 211 (and/or 221) (such
as, for example, one or more internal registers or caches), one or
more portions of memory 213 (and/or 223), one or more portions of
storage 215 (and/or 225), or a combination of these, where
appropriate. In particular embodiments, a computer-readable storage
medium implements RAM or ROM. In particular embodiments, a
computer-readable storage medium implements volatile or persistent
memory. In particular embodiments, one or more computer-readable
storage media embody encoded software.
[0045] Herein, reference to encoded software may encompass one or
more applications, bytecode, one or more computer programs, one or
more executables, one or more instructions, logic, machine code,
one or more scripts, or source code, and vice versa, where
appropriate, that have been stored or encoded in a tangible,
non-transitory computer-readable storage medium. In particular
embodiments, encoded software includes one or more application
programming interfaces (APIs) stored or encoded in a
computer-readable storage medium. Particular embodiments may use
any suitable encoded software written or otherwise expressed in any
suitable programming language or combination of programming
languages stored or encoded in any suitable type or number of
computer-readable storage media. In particular embodiments, encoded
software may be expressed as source code or object code. In
particular embodiments, encoded software is expressed in a
higher-level programming language, such as, for example, C, Perl,
or a suitable extension thereof. In particular embodiments, encoded
software is expressed in a lower-level programming language, such
as assembly language (or machine code). In particular embodiments,
encoded software is expressed in JAVA. In particular embodiments,
encoded software is expressed in Hyper Text Markup Language (HTML),
Extensible Markup Language (XML), or other suitable markup
language.
[0046] The components and devices illustrated in FIG. 2 form
distributed antenna system 200. From the perspective of an
endpoint, distributed antenna system 200 may appear as a single
base station. An endpoint may be unable to distinguish between a
wireless transmission sent by remote transceiver 220a and a
wireless transmission sent by remote transceiver 220b. The channel
experienced by an endpoint is the sum of the channel responses from
each of remote transceivers 220. In particular embodiments, base
station 210 may communicate with remote transceivers 220 using
Common Public Radio Interface (CPRI). The CPRI specification
supports a variety of topologies, including ring, tree, star, and
chain topologies. The CPRI specification allows multiple remote
transceivers 220 to be controlled by the same base station 210. In
some embodiments, a CPRI link may be used by base station 210 to
send/receive different in-phase/quadrature (I/Q) data to/from each
different remote transceivers 220. For example, in some
embodiments, base station 210 may apply the power distribution
locally. This may result in each remote transceiver needing its own
unique I/Q sample. In particular embodiments, the CPRI link may be
used to send/receive a single set of I/Q samples from remote
transceivers 220. For example, in some embodiments the power
distribution may be applied individually at each respective remote
transceiver. This may allow a single I/Q sample to be used by all
remote transceivers 220.
[0047] The allocation of power to different subcarriers at
different remote transceivers 220 for different endpoints in the
power distribution may be based on the signal quality (e.g., the
received power) associated with communications sent from each
endpoint and received at each remote transceiver 220. In particular
embodiments, base station 210 may allocate more power to those
endpoints having better channel quality at each respective remote
transceiver. Depending on the embodiment, there may be at least
three components used to determine channel response: path loss,
shadowing, and multipath. In contrast with shadowing and multipath
effects (which are often random processes) path loss is the most
dominant component in the channel response. Path loss may be a
function of the distance between an endpoint and a remote
transceiver. The closer an endpoint is to a particular remote
transceiver, the higher the channel gain is between the endpoint
and the remote transceiver. In distributed antenna system 200, the
varying distances between an endpoint and each remote transceiver
220 may result in varying path losses and channel gains between
remote transceivers 220 a particular endpoint.
[0048] In particular embodiments, the closer an endpoint is to a
remote transceiver, the greater the power that will be allocated to
the subcarriers associated with the endpoint. Conversely, the
farther an endpoint is from a remote transceiver, the less power
that will be allocated to subcarriers associated with the endpoint.
This may allow each remote transceiver 220 to more efficiently use
their available transmission power. The non-uniform power
distribution to different subcarriers could enhance the signal to
interference-plus-noise ratio (SINR) at the endpoint by increasing
the received signal strength from the closer remote transceivers
220 while the loss of signal strength due to the reduced power from
a more distant remote transceiver may be insignificant.
[0049] In particular embodiments, each remote transceiver 220 may
measure the average received power of the subcarriers allocated to
each endpoint. This information may then be delivered to base
station 210 over a CPRI control channel. Base station 210 may use
the measured uplink power to approximate the downlink channel
response between each remote transceiver 220 and the endpoints.
This estimation may be used by base station 210 to determine the
power distribution which base station 210 may then send to remote
transceivers 220 using the CPRI control channel.
[0050] In some embodiments, each remote transceiver 220 may send
their own respective I/Q data along with I/Q data received from the
upstream remote transceiver. Base station 210 may use the
individual I/Q samples to estimate the received downlink power at
the endpoint (e.g., it may be proportional to the determined uplink
power). Using this estimated power, base station 210 may determine
and apply an amount of amplification or attenuation to the download
signal. This may be done without adjusting the phase of the
download signal. The amplified data may then be sent to remote
transceivers 220 as individual I/Q data.
[0051] In certain embodiments, before base station 210 allocates
the distribution of power, it may first execute a scheduling
algorithm to allocate subcarriers within a channel to the different
endpoints. Once the subcarriers have been assigned, base station
210 may use the measured uplink power received from remote
transceivers 220 to redistribute the downlink power to maximize
system capacity. Depending on the embodiment and/or scenario, base
station 210 could use any of a variety of strategies to apply power
distribution. For example, base station 210 may be able to
determine an optimum power distribution by applying KKT optimality
conditions with the following optimization formula:
max { G r u } f ( G ) = m = 1 N M S m ln ( 1 + r = 1 N R K r m G r
m ) ##EQU00001## s . t . m = 1 N M S m G r m = N .A-inverted. r = 1
, , N R ##EQU00001.2## G r m .gtoreq. 0 .A-inverted. r = 1 , , N R
; m = 1 , , N M ##EQU00001.3##
in which: (1) S.sub.m may represent the number of subcarriers
allocated to endpoint m; (2) G.sub.rm may represent the power
amplification factor at remote transceiver r for all the
subcarriers allocated to endpoint m; (3) K.sub.rm may represent the
indicator of signal quality which may be proportional to the power
received by remote transceiver r from endpoint m; (4) N may
represent the number of subcarriers in a channel; (5) N.sub.R may
represent the number of remote transceivers controlled by base
station 210; and (6) N.sub.M may represent the number of the
endpoints which are scheduled by base station 210 to receive data
in one frame.
[0052] In certain embodiments, base station 210 may use the
following Lagrangian function of the optimization problem in
determining an optimum power distribution:
L ( G , .lamda. , .mu. ) = m = 1 N M - S m ln ( 1 + r = 1 N R K r m
G r m ) ) + r = 1 N R .lamda. r ( m = 1 N M S m G r m - N ) - r = 1
N R m = 1 N M .mu. r m G r m ##EQU00002##
in which .mu. and .lamda. are Lagrangian coefficients.
[0053] In certain embodiments, the equations associated with the
KKT optimality conditions may be expressed as follows:
.differential. L .differential. G r m = 0 j = 1 N R K j m G j m - S
m K r m S m .lamda. r - .mu. r m = - 1 .A-inverted. r = 1 , , N R ;
m = 1 , , N M ( KKT 1 ) m = 1 N M S m G r m = N .A-inverted. r = 1
, , N R ( KKT 2 ) G r m .gtoreq. 0 .A-inverted. r = 1 , , N R ; m =
1 , , N M ( KKT 3 ) .mu. r m G r m = 0 .A-inverted. r = 1 , , N R ;
m = 1 , , N M ( KKT 4 ) .mu. r m .gtoreq. 0 .A-inverted. r = 1 , ,
N R ; m = 1 , , N M ( KKT 5 ) ##EQU00003##
The variables in equations KKT 1 through KKT 5 include G.sub.rm,
.lamda..sub.r, and .mu..sub.rm in which the number of variables are
(N.sub.RN.sub.M), N.sub.R, and (N.sub.RN.sub.M), respectively
(N.sub.R may represent the number of remote transceivers and
N.sub.M may represent the number of endpoints which are scheduled
by base station 210 to receive data in one frame). Thus, the total
number of variables in the KKT optimality condition equations may
be (2N.sub.RN.sub.M+N.sub.R). Fortunately, there also exist
(2N.sub.RN.sub.M+N.sub.R) KKT optimality equations in KKT 1, 2, and
4. By solving these three sets of equations, it may be possible to
find a global optimal solution.
[0054] Particular embodiments, may avoid the time and/or
computational cost of solving the non-linear equation of KKT 1 and
4, by using an intelligent heuristic algorithm to transform KKT 1
and 4 into a linear problem that may be solved in a greedy manner.
When G.sub.rm, the power amplification factor of endpoint m at
remote transceiver r, is positive the corresponding Lagrangian
multiplier, .mu..sub.rm, is equal to zero (see e.g., KKT 4). Then,
KKT 1 may be simplified as a linear equation of {G.sub.jm}
j=1.about.N.sub.R and the inverse of the Lagrangian multiplier,
.lamda..sub.r:
j = 1 N R K j m G j m - K r m .lamda. r = - 1 ##EQU00004##
If it is assumed that the set of the positive power amplification
gain, {G.sub.rm>0}, is known, the KKT optimality conditions
equations can be transformed into linear equations: AX=B, where:
[0055] 1) X is a (N.sub.RN.sub.M+N.sub.R).times.1 column
vector,
[0055] X=(G.sub.11, . . . ,G.sub.N.sub.R.sub.1,G.sub.12, . . .
,G.sub.N.sub.R.sub.2, . . . ,G.sub.1N.sub.M, . . .
,G.sub.N.sub.R.sub.N.sub.M,1/.lamda..sub.1, . . .
,1/.lamda..sub.N.sub.R).sup.T [0056] 2) A is a
(N.sub.RN.sub.M+N.sub.R).times.(N.sub.RN.sub.M+N.sub.R) square
matrix. Its ((y-1). N.sub.R+x)-th row corresponds to the equation
of G.sub.r=x,m=y in KKT 1. If G.sub.xy is greater than zero, the
((y-1)N.sub.R+x)-th row vector is:
[0056] [ 0 0 0 ( y - 1 ) N R 0 s K 1 y K N R y 0 0 0 ( N M - y ) N
R 0 s 0 0 0 ( x - 1 ) - K x y 0 0 ] ##EQU00005## [0057] On the
other hand, if G.sub.xy is equal to zero, the ((y-1). N.sub.R+x)-th
row vector of the matrix A can be simply the row vector with all
elements equal to zero except the ((y-1)N.sub.R+x)-th element which
may be equal to one
[0057] ( e . g . , 0 0 0 0 ( y - 1 ) N R + ( x - 1 ) 0 s 1 0 0 ) .
##EQU00006## [0058] The (N.sub.RN.sub.M+r)-th (r=1.about.N.sub.R)
row vector of the matrix A may correspond to an equation in KKT 2.
The (N.sub.RN.sub.M+1)-th to (N.sub.RN.sub.M+N.sub.R)-th row
vectors can presented as a concatenation of a series of N.sub.M
scalar matrices and a zero matrix:
[0058] [a.sub.ij]i=N.sub.RN.sub.M+1, . . .
,N.sub.RN.sub.M+N.sub.R;j=1, . . .
,N.sub.RN.sub.M+N.sub.R=(S.sub.1I.sub.N.sub.R, . . .
,S.sub.N.sub.MI.sub.N.sub.R,0.sub.N.sub.R) [0059] where
I.sub.N.sub.R is the N.sub.R.times.N.sub.R identity matrix. [0060]
3) B is a (N.sub.RN.sub.M+N.sub.R).times.1 column vector. Its
((y-1)N.sub.R+x)-th element, B(y-1)N.sub.R+x, is equal to -1 if
G.sub.xy is greater than zero; otherwise, B(y-1)N.sub.R+x is equal
to zero. The (N.sub.RN.sub.M+1)-th to (N.sub.RN.sub.M+N.sub.R)-th
elements of the vector B may all be equal to N.
[0061] In certain embodiments, the elements of the matrices A and B
may depend on the selection of positive power amplification gain.
Thus, base station 210 may select a subset of combinations from
among all the possible combinations of endpoints and remote
transceivers before transforming the KKT equations into linear
equations. However, it may not be desirable to try every possible
combination because the total number of possible combinations may
grow exponentially. Rather, certain embodiments may use an
intelligent heuristic algorithm to identify the candidates of the
positive power amplification gain in a greedy manner.
[0062] In certain instances, the algorithm may begin by searching
for an initial set {G.sub.rm} of pairings with positive power
amplification gain. Each pairing may represent a combination of one
endpoint and one remote transceiver. For example, if there were two
endpoints in the depicted embodiment, there would be six pairings
((2 endpoints)*(3 remote transceivers)=6 pairing). Based on the
equality constraint in KKT 2, for each remote transceiver r, there
exists at least one positive power amplification gain,
G.sub.rm>0, assigned to an endpoint m. In certain embodiments
and/or scenarios, pairings having a higher received power (e.g.,
higher K.sub.rm value as discussed below) may result in a higher
objective value. The objective value may be derived from the
objective function which may be designed to distribute power so as
to maximize the overall system capacity. Thus, certain embodiments
may, for each remote transceiver, select the pairing having the
highest received power. Moreover, to ensure that each endpoint has
at least some positive power amplification gain for at least one
remote transceiver, base station 210 may, for each endpoint that is
not included in any of the initially selected pairings, determine
the pairing having the greatest received power.
[0063] In some embodiments, the indicator of signal quality, which
may be proportional to the received power, may be computed as
K r m = c P r m U L N T .sigma. n 2 ##EQU00007##
where c may represent a constant used to calibrate the differences
between the transmitting and receiving antenna gains of downlink
and uplink connections; P.sub.rm.sup.UL may represent the average
of the received uplink power of a subcarrier allocated to the m-th
endpoint at the r-th remote transceiver; N.sub.T may represent the
number of the transmitting antennas at each remote transceiver; and
.sigma..sub.n.sup.2 may represent the variance of the noise power
per subcarrier.
[0064] After determining the initial set of positive power gain
{G.sub.rm>0}, the matrices A and B may be determined and used to
solve linear equations of A*X=B. The solution to X may be a
potential solution of the optimization problem, {G.sub.rm}. This
potential solution may be compared with a previous solution to
determine whether the value of the objective function is improved.
If the value of the objective function, based on the potential
solution, is an improvement over the previous solution, then the
potential solution may be accepted for the possible final solution.
The potential solution may then be tested to determine if it
satisfies the KKT optimality conditions (e.g., KKT 1-5).
[0065] In certain embodiments, the Lagrangian multiplier,
.mu..sub.rm can be computed as:
.mu. r m = S m ( .lamda. r - K r m 1 + j = 1 N R K j m G j m )
##EQU00008##
Then a check may be made to determine if the set of the complete
solution {G.sub.rm, .lamda..sub.r, and .mu..sub.rm} satisfies the
KKT condition equations by computing one or more individual error
values based on:
Error r m = j = 1 N R K j m G j m - S m K r m S m .lamda. r - .mu.
r m + 1 ##EQU00009## .A-inverted. r = 1 , , N R ; m = 1 , , N M
##EQU00009.2##
If all Error.sub.rm values are below a tolerance threshold then the
solution satisfies the KKT optimality condition equations and may
be considered a global optimal solution.
[0066] On the other hand, if one or more Error.sub.rm values exceed
the tolerance threshold then the potential solution may not be
considered to be the optimal solution since it does not satisfy the
KKT conditions. If this occurs, then the next candidate for a
positive power gain is determined to improve the objective
value.
[0067] In some embodiments, a heuristic approach may be used to
determine the next candidate pairing of positive G.sub.xy from the
descending order of {K.sub.rm} r=1.about.N.sub.R,
m=1.about.N.sub.M. In certain embodiments, before the next
candidate is considered, a potential next candidate may be tested
to determine if it will increase the result of the objective
function without solving the converted linear equations. For
example, the potential next candidate G.sub.xy may be used improve
the objective value if the following inequality holds:
K x y 1 + j = 1 N R K j y G j y > K x m 1 + j = 1 N R K j m G j
m .A-inverted. any G x m > 0 ##EQU00010##
[0068] Once the next candidate has been determined, both matrices A
and B may be updated. The ((y-1)N.sub.R+x)-th row of the matrix A
may be replaced by the row vector
[ 0 0 0 ( y - 1 ) N R 0 s K 1 y K N R y 0 0 0 ( N M - y ) N R 0 s 0
0 0 ( x - 1 ) - K x y 0 0 ] ##EQU00011##
while the ((y-1)N.sub.R+x)-th element in vector B may be changed
from 0 to -1. The new solution may be obtained by solving the
linear equations based on the updated matrices A and B.
[0069] The above algorithm may be repeated until either a solution
is found that satisfies the KKT optimality conditions or the last
candidate with the smallest received power (e.g., the smallest
K.sub.rm) is evaluated. In the worst case, there may be at most
(N.sub.RN.sub.M) iterations. The computing time in each iteration
may be based on spending at most O(N.sub.R.sup.zN.sub.M.sup.z) in
solving linear equations. Therefore, the complexity of the proposed
algorithm may be O(N.sub.R.sup.3N.sub.M.sup.3).
[0070] Once base station 210 has determined how to allocate the
downlink power for the various subcarriers at each remote
transceiver 220, the power distribution may be applied either at
base station 210 or at remote transceivers 220. For example, in
some embodiments, base station 210 may generate I/Q data for each
remote transceiver 220 that includes the core data modified by the
power distribution (this may be done in the frequency domain before
base station 210 performs Inverse Discrete Fourier Transform (IDFT)
operations). As another example, in some embodiments, base station
210 may send the core data and power distribution information
separately. For example, the core data may be sent via the CPRI
data link, and the power distribution information may be sent via
the CPRI control session. This may allow each remote transceiver
220 to apply the power distribution locally. This may further allow
base station 210 to send the same (frequency-domain) data to each
remote transceiver 220 thereby reducing the data rate needed for
the CPRI link.
[0071] Thus far, several different embodiments and features have
been presented. Particular embodiments may combine one or more of
these features depending on operational needs and/or component
limitations. This may allow for great adaptability of distributed
antenna system 200 to the needs of various organizations and users.
Some embodiments may include additional features.
[0072] FIG. 3A illustrates a method for implementing power
distribution, in accordance with a particular embodiment. FIG. 3B
illustrates several sample models to help illustrate corresponding
steps in the method depicted in FIG. 3A, in accordance with a
particular embodiment. The sample models depicted in FIG. 3B are
numbered to correspond to a respective step in the method depicted
in FIG. 3A. For example, the signal quality matrix depicted in
model 315b corresponds to step 315. For purposes of simplicity, the
illustrated steps of the method for the depicted embodiment are
from the perspective of a base station. The base station is
responsible for managing a plurality of remote transceivers in a
distributed antenna system.
[0073] The method begins at step 305 with the establishment of
connections between a base station and a plurality of remote
transceivers. In some embodiments the connection between the base
station and the plurality of remote transceivers may comprise a
Common Public Radio Interface connection. At step 310 a plurality
of wireless connections are established with a plurality of
endpoints. The wireless connections are established via one or more
of the plurality of remote transceivers. While each endpoint, from
its perspective, may have established a single wireless connection
with a single base station, each endpoint may actually be sending
and receiving communications from a number of remote transceivers.
It may be helpful to think of these connections as pairings. A
pairing may represent a connection between one remote transceiver
and one endpoint.
[0074] Model 310b depicts a scenario in which wireless connections
are established with two endpoints (EP-A and EP-B) via three remote
transceivers (RT-X, RT-Y, and RT-Z). This configuration results in
six unique pairings (XA, XB, YA, YB, ZA, and ZB). More
specifically, there are two pairings (one for each of endpoints
(EP-A and EP-B) associated with each of the three remote
transceivers (RT-X, RT-Y, and RT-Z).
[0075] At step 315 a signal quality is determined for each unique
pairing. Each signal quality indication may comprise information
from which the base station may be able to determine the relative
quality, strength, and/or efficiency of a wireless connection
between the respective remote transceiver and the respective
endpoint. For example, if a particular remote transceiver is able
to receive a signal from two endpoints, the signal quality
indication sent from the particular remote transceiver would
include information regarding the relative quality, strength,
and/or efficiency of a wireless connection with both of the two
endpoints. In certain embodiments, the signal quality indication
may be based on the received power. That is, the signal quality
associated with pairing XA may be based on the received power of a
communication from EP-A received by RT-X. Model 315b illustrates an
R by M sized signal quality matrix, K.sub.RM, in which R is the
number of remote transceivers (three) and M is the number of
endpoints (two). The values provided are to aid in the example and
do not necessarily represent actual signal quality values or
received power values.
[0076] At step 320 a power matrix is generated based on the
determined signal quality. The power matrix may comprise the same
dimensions as the signal quality matrix. In certain embodiments,
the power matrix may be initialized to all 0s. This is shown in
model 320b-1. Next, for each remote transceiver, the endpoint
having the highest received power is noted as a 1 in the
corresponding element of the power matrix. This is shown in model
320b-2. In particular, endpoint EP-A has the best signal at each of
the three remote transceivers. Next, for each endpoint that has not
been assigned any positive power gain, the remote transceiver with
the best signal for that endpoint is noted as a 1 in the
corresponding element of the power matrix. In model 320b-2 it can
be seen that there are no is for endpoint EP-B, thus a 1 is noted
for the ZB pairing because the signal from endpoint EP-B is best
received at remote transceiver RT-Z. This is shown in model
320b-3.
[0077] At step 325 a potential solution is determined to linear
equations using the power matrix. In some embodiments, the linear
equation may be of the form A*X=B, where the solution for X is the
potential solution. As discussed in more detail below, A and B may
be formed based on the power matrix and the signal quality for each
pairing.
[0078] A is a
(N.sub.RN.sub.M+N.sub.R).times.(N.sub.RN.sub.M+N.sub.R) square
matrix (9.times.9 in FIG. 3B). Its ((y-1)N.sub.R+x)-th row
corresponds to the equation of G.sub.r=x,m=y in KKT 1. If G.sub.xy
is greater than zero, the ((y-1)N.sub.R+x)-th row vector is:
[ 0 0 0 ( y - 1 ) N R 0 s K 1 y K N R y 0 0 0 ( N M - y ) N R 0 s 0
0 0 ( x - 1 ) - K x y 0 0 ] . ##EQU00012##
On the other hand, if G.sub.xy is equal to zero, the
((y-1)N.sub.R+x)-th row vector of the matrix A can be simply the
row vector with all elements equal to zero except for the
((y-1)N.sub.R+x)-th element equal which may be equal to one
( e . g . , 0 0 0 0 ( y - 1 ) N R + ( x - 1 ) 0 s 1 0 0 ) .
##EQU00013##
[0079] The (N.sub.RN.sub.M+r)-th (r=1.about.N.sub.R) row vector of
the matrix A may correspond to an equation in KKT 2. The
(N.sub.RN.sub.M+1)-th to (N.sub.RN.sub.M+N.sub.R)-th row vectors
may be presented as a concatenation of a series of N.sub.M scalar
matrices and a zero matrix:
[a.sub.ij]i=N.sub.RN.sub.M+1, . . . ,N.sub.RN.sub.M+N.sub.R;j=1, .
. . ,N.sub.RN.sub.M+N.sub.R=(S.sub.1I.sub.N.sub.R, . . .
,S.sub.N.sub.MI.sub.N.sub.R,0.sub.N.sub.R)
where I.sub.N.sub.R is the N.sub.R.times.N.sub.R identity matrix.
For simplicity, the value of the number of subcarriers assigned to
each endpoint is represented by the letter Q and elements of the
(N.sub.RN.sub.M+1)-th to (N.sub.RN.sub.M+N.sub.R)-th row are
represented in matrix A in model 325b.
[0080] B is a (N.sub.RN.sub.M+N.sub.R).times.1 column vector. Its
((y-1)N.sub.R+x)-th element, B(y-1)N.sub.R+x, is equal to -1 if
G.sub.xy is greater than zero; otherwise, B(y-1)N.sub.R+x is equal
to 0. The (N.sub.RN.sub.M+1)-th to (N.sub.RN.sub.M+N.sub.R)-th
elements of the vector B may all be equal to N, the number of
subcarriers in a channel.
[0081] Once A and B have been defined, the equation A*X=B may be
solved for X. X is a (N.sub.RN.sub.M+N.sub.R).times.1 column
vector,
X=(G.sub.11, . . . ,G.sub.N.sub.R.sub.1,G.sub.12, . . .
,G.sub.N.sub.R.sub.2, . . . ,G.sub.1N.sub.M, . . .
,G.sub.N.sub.R.sub.N.sub.M,1/.lamda..sub.1, . . .
,1/.lamda..sub.N.sub.R).sup.T,
where N.sub.R is the number of remote transceivers (three in FIG.
3B) and N.sub.M is the number of endpoints (two in FIG. 3B). The
resulting X may comprise the solution of power gains for each pair
of remote transceiver and endpoint (indicated as G above) and
Lagrangian multipliers (indicated as .lamda. above). The value of
the objective function may be computed based on the solution of
power gains. At step 330 the potential solution is compared to a
previous solution to determine if the potential solution is an
improvement. In certain embodiments, the comparison may be between
the determined objective function and a previously determined
objective function. At decision step 335, if the potential solution
is an improvement over the previous solution the method continues
to step 340, otherwise the method continues to step 350.
[0082] At step 350 the power matrix is modified. The modification
may comprise updating the entry of one or more pairings in the
power matrix. The updated entry may correspond to the next best
signal determined from among the signals that have not already been
identified. For example, the value associated with pairing XB in
the power matrix may be updated to 1 because pairing XB has a
better signal than pairing YB. In some embodiments, the power
matrix may be modified by including a pairing that satisfies the
following conditions:
K x y 1 + j = 1 N R K j y G j y > K x m 1 + j = 1 N R K j m G j
m .A-inverted. any G x m > 0 ##EQU00014##
[0083] At step 340 one or more error values may be determined based
on the potential solution. The error values may be determined using
the following equation:
Error r m = j = 1 N R K j m G j m - S m K r m S m .lamda. r - .mu.
r m + 1 ##EQU00015## .A-inverted. r = 1 , , N R ; m = 1 , , N M .
##EQU00015.2##
[0084] At decision step 345, if one or more of the resulting
Error.sub.rm values are greater than a threshold value, then the
method proceeds to step 350 (discussed above); if the Error.sub.rm
values are below the threshold, then the method proceeds to step
355. If the Error.sub.rm values are below the threshold, it may be
determined that the potential solution satisfies the KKT optimality
condition equations and is the global optimal solution.
[0085] At step 355 a power distribution is determined for each
endpoint at each remote transceiver based on the potential
solution. The power distribution determines the amount of
amplification each remote transceiver is to use when transmitting
wireless communications to each of the endpoints. In certain
embodiments, the better (e.g., stronger, clearer, more efficient) a
wireless signal is between a remote transceiver and an endpoint,
the greater the amount of power the remote transceiver will use to
communicate with the endpoint; conversely the worse a wireless
signal is, the less power the remote transceiver will use to
communicate with the endpoint. Thus, the power distribution may not
be uniform among the endpoints and/or remote transceivers
[0086] Some of the steps illustrated in FIG. 3A may be combined,
modified or deleted where appropriate, and additional steps may
also be added to the flowchart. Additionally, steps may be
performed in any suitable order without departing from the scope of
particular embodiments.
[0087] While various implementations and features are discussed
with respect to multiple embodiments, it should be understood that
such implementations and features may be combined, re-arranged or
modified in various embodiments. For example, features and
functionality discussed with respect to a particular figure, such
as FIG. 2, may be used in connection with features and
functionality discussed with respect to another such figure, such
as FIG. 1, according to operational needs or desires.
[0088] Although particular embodiments have been described in
detail, it should be understood that various other changes,
substitutions, and alterations may be made hereto without departing
from the spirit and scope of particular embodiments. For example,
although an embodiment has been described with reference to a
number of elements included within distributed antenna system 100
such as endpoints, base stations and remote transceivers, these
elements may be combined, rearranged or positioned in order to
accommodate particular routing architectures or needs. In addition,
any of these elements may be provided as separate external
components to distributed antenna system 100 or each other where
appropriate. Particular embodiments contemplate great flexibility
in the arrangement of these elements as well as their internal
components.
[0089] Numerous other changes, substitutions, variations,
alterations and modifications may be ascertained by those skilled
in the art and it is intended that particular embodiments encompass
all such changes, substitutions, variations, alterations and
modifications as falling within the spirit and scope of the
appended claims.
* * * * *