U.S. patent application number 10/281907 was filed with the patent office on 2003-07-10 for system and method for frequency planning in wireless communication networks.
Invention is credited to Davidor, Yuval, Tanay, Amos.
Application Number | 20030129987 10/281907 |
Document ID | / |
Family ID | 24550166 |
Filed Date | 2003-07-10 |
United States Patent
Application |
20030129987 |
Kind Code |
A1 |
Tanay, Amos ; et
al. |
July 10, 2003 |
System and method for frequency planning in wireless communication
networks
Abstract
A system and method for frequency planning in a wireless
communication network area using an impact matrix which relates
signal interference impacts between sectors in a network service
area for co-channel and adjacent channel interference. The impact
matrix uses weighted propagation analysis and empirical measurement
data to determine signal levels within each pixel of a network
service area. The system merges the propagation analysis and
empirical measurement data according to user assigned
confidences.
Inventors: |
Tanay, Amos; (Tel-Aviv,
IL) ; Davidor, Yuval; (Moshav Avihail, IL) |
Correspondence
Address: |
BROWN, RAYSMAN, MILLSTEIN, FELDER & STEINER LLP
900 THIRD AVENUE
NEW YORK
NY
10022
US
|
Family ID: |
24550166 |
Appl. No.: |
10/281907 |
Filed: |
October 28, 2002 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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10281907 |
Oct 28, 2002 |
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09636044 |
Aug 10, 2000 |
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6487414 |
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Current U.S.
Class: |
455/450 |
Current CPC
Class: |
H04W 16/18 20130101 |
Class at
Publication: |
455/450 ;
455/63 |
International
Class: |
H04B 001/10; H04B
015/00; H04Q 007/20 |
Claims
What is claimed is:
1. A method of generating an impact matrix for use in allocating
frequency channels in a wireless communication network service
area, the network area divided into a plurality of sectors which
are further divided into a plurality of pixels, the impact matrix
providing impact scores which characterizes sector by sector
channel interference in the network service area, the method
comprising: merging signal propagation analysis data and empirical
measurement data to determine an anticipated signal level for each
one of the plurality of pixels in the network service area;
determining which one of the sectors in the network service area is
a serving sector for the pixel; determining channel interference
impact scores for the pixel based on the interference between the
pixel's serving sector and each of the other sectors in the network
service area; and providing sector by sector impact scores.
2. The method of claim 1, wherein merging propagation analysis is
performed according to user ascribed confidences.
3. The method of claim 1, wherein determining channel interference
impact scores between the pixel's serving sector and signals from
each of the other sectors in the network service area comprises:
calculating ratios between a signal from the serving sector and
signal levels from each of the other sectors in the network service
area; assigning unweighted interference impact scores based in part
on the calculated ratios; and adjusting unweighted interference
impact scores according to user assigned variables.
4. The method of claim 3, wherein the user assigned variables
comprise network area sensitivity to call quality and amount of
call volume for that network service area.
5. The method of claim 1, further comprising modifying the overall
impact scores in the impact matrix according to channel pairing
relationships among sectors which are known to provide high levels
and low levels of interference.
6. The method of claim 5, further comprising modifying the overall
impact scores in the impact matrix according to detailed call
history information.
7. The method of claim 6, wherein the detailed call history
information includes dropped call information.
8. A system for developing an impact matrix for use in frequency
channel planning in a wireless communication network service area,
the communication network service area divided into sectors and
pixels, the system comprising: means for determining a signal
strength level for each pixel in the network service area; means
for determining which is a serving sector for each pixel in the
network service area; means for determining an interference impact
score between each pixel's serving sector and each of the other
non-serving sectors in the network service area; and means for
determining overall sector by sector impact scores for inclusion in
the impact matrix, the overall sector by sector impact scores based
on the interference impact scores for the pixels within which a
sector is the serving sector.
9. The system of claim 8, wherein the means for determining a
signal strength for each pixel in the network service area
comprises means for conducting a propagation analysis and means for
performing empirical measurements.
10. The system of claim 8, wherein the means for determining an
interference impact score between each pixel's serving sector and
each of the other non-serving sectors in the network service area
comprises: means for calculating for each of the other non-serving
sectors in the network service area, the ratio between the signal
strength level from the serving sector and a signal strength level
from each of the other non-serving sectors; means for assigning
interference impact scores for each of the non-serving sectors; and
means for weighting the interference impact scores.
11. The system of claim 10, wherein the means for weighting the
interference impact score comprises means for allowing the user to
specify sensitive areas within the communication network service
area.
12. The system of claim 11, wherein the means for weighting the
interference impact score comprises means for allowing the user to
specify areas having high or low call volume within the
communication network service area.
13. The system of claim 8, further comprising means for modifying
the impact matrix based on data which specifies co-channel
assignments which will not result in excessive interference.
14. The system of claim 13, further comprising means for modifying
the impact matrix based on data which specifies co-channel
assignments which will result in excessive interference.
15. The system of claim 14, further comprising means for modifying
the impact matrix based on data which specifies adjacent channel
assignments which will not result in excessive interference.
16. The system of claim 15, further comprising means for modifying
the impact matrix based on data which specifies adjacent channel
assignments which will result in excessive interference.
17. The system of claim 16, further comprising means for modifying
the impact matrix based on call detail information.
18. The system of claim 17, wherein the call detail information
includes at least one or more of the following: time of call drops,
channel in use by dropped calls, serving sectors of dropped calls,
time dropped calls began, initial channel assigned to dropped
calls, initial serving sector of dropped calls, call handoff
information and time calls ended.
19. The system of claim 8, wherein the impact matrix allows a user
to make and evaluate individual channel assignments in the
communication network.
20. A computer implemented process for creating an impact matrix
for use in allocating channels in a wireless network which is
divided into sectors, the impact matrix constructed based on a
pixel by pixel analysis of signal interference within the network,
the process comprising: determining a serving sector for at least
one pixel in the network; determining weighted interference impact
scores for the at least one pixel, the weighted interference impact
scores based upon each of the non-serving sectors' interference
impact upon the pixel's serving sector; and determining overall
impact scores based upon the weighted interference impact scores
for the at least one pixel.
21. The process of claim 20, wherein determining a serving sector
for at least one pixel in the network comprises merging propagation
analysis and empirical data according to user ascribed confidences
assigned to the data.
22. The process of claim 20, wherein determining overall impact
scores comprises, for all of the pixels in the network for which a
specific sector is the serving sector, processing all of the
weighted interference impact scores for those pixel based upon the
interference impact between the pixels' serving sector and each of
the other non-serving sectors in the network.
23. A method of using an impact matrix for frequency channel
planning in a wireless communication network divided into sectors,
the impact matrix providing sector by sector signal quality
interference ratings, the method comprising: determining an
incremental quality degradation for a potential channel assignment
in the network using the impact matrix; and assigning frequency
channels to sectors according to the incremental quality
degradation provided by the impact matrix.
24. The method of claim 23, wherein the impact matrix provides
co-channel interference ratings.
25. The method of claim 23, wherein the impact matrix provides
adjacent channel interference ratings.
26. A computer readable medium containing a program which when
executed on a computer causes the computer to perform a method for
creating an impact matrix for use in frequency channel planning in
a network service area which is divided into a plurality of pixels,
the method comprising: determining a serving sector for each of the
plurality of pixels in the network; determining weighted
interference impact scores for the selected pixel, the weighted
interference impact scores based upon each of the non-serving
sectors' interference impact upon the pixel's serving sector; and
determining overall impact scores based upon the weighted
interference impact scores, wherein the impact matrix characterizes
the interference relationship between sectors in the network
service area.
Description
COPYRIGHT NOTICE
[0001] A portion of the disclosure of this patent document contains
material which is subject to copyright protection. The copyright
owner has no objection to the facsimile reproduction by anyone of
the patent document or the patent disclosure, as it appears in the
Patent and Trademark Office patent files or records, but otherwise
reserves all copyright rights whatsoever.
BACKGROUND OF THE INVENTION
[0002] This invention relates generally to the field of frequency
planning in wireless communication networks and, in particular, to
a system and method for improved consideration of the impact of
various factors in frequency planning.
[0003] In wireless communication systems, such as a cellular mobile
radio communication system, the geographic area served by the
system is divided into geographically defined cells. In the system,
there is a finite number of carrier frequency channels, typically
radio-frequency (RF) channels, that are available for use during
communications in and between network areas cells. Typically, a
frequency group, consisting of a subset of all of the available
frequencies, is assigned to each cell for that cell's use during
communications.
[0004] However, because the number of frequency groups is limited,
it is necessary to reuse them within the area served by the system.
To provide for a greater coverage by the system, and to provide for
greater capacity through higher reuse of frequency groups, the
network service area cells may be further divided up into sectors.
Because the use of a particular frequency by two different sectors
can result in interference during a call or even result in the call
being completely cut-off or "dropped", an effort must be made to
assign frequency groups to sectors in a manner that minimizes the
amount of interference.
[0005] In wireless communication networks, there are two primary
types of interference: co-channel interference and neighbor or
adjacent channel interference. Co-channel interference is the
interference from communication sources tuned to the same frequency
as the operating channel. Adjacent-channel interference comes from
communication sources using channels near the operating channel in
the frequency domain. To achieve the desired voice or data
transmission quality, the ratio of the received signal over the
combined co-channel and neighbor-channel interference must be above
a specified threshold. Such channel interference can be up-link or
down-link interference or a combination of these interferences.
Down-link interference is channel interference received at regions
serviced by a first base station caused from signals transmitted by
other base stations. Up-link interference is interference at the
base stations caused from signals transmitted by mobile units in
regions of the coverage area that are not serviced by that base
station.
[0006] Furthermore, other factors such as antenna patterns, power
levels, scattering, and wave diffraction variations combined with
buildings, various other structures, hills, mountains, foliage, and
other physical objects contribute to the interference experienced
during wireless communications.
[0007] In frequency planning for a wireless communication network,
the primary task is to try to predict and attempt to reduce the
amount of channel interference experienced by strategically
assigning certain channels to certain sectors. Typically, this can
be achieved by assigning frequencies so that the distance between
co-channel and adjacent channel sectors is maximized. In this
context, "distance" does not necessarily refer to geographic
distance but connotes a distance in the RF sense. That is, although
sectors far apart from each other geographically are less likely to
"see" each other, they can still interfere with each other. For
example, a high sector can interfere with a sector as far as
hundreds of miles away. Maximizing this distance decreases the
chances of the sectors conflicting with one another in the
airwaves. However, a severe consequence of maximizing this distance
is that it effectively reduces the amount of channel combinations
possible in the network service area, thereby limiting the amount
of coverage available for wireless communication. Typically,
frequency planning is ordinarily accomplished by three primary
techniques including channel sets, reuse patterns and pixel based
interference analysis.
[0008] Channel sets are non-overlapping subsets of the available
channels organized according to a periodic frequency spacing in
terms of number of channels between members of a given set. The
principal disadvantage of using channel sets is that the number of
channels required from sector to sector usually varies, and optimal
frequency planning will require that just that number, rather than
the number in an arbitrary set, be assigned to each sector.
[0009] In the reuse pattern scheme, the sectors in a network are
arranged in a two-dimensional pattern, or "grid". Channels or, more
commonly, channel sets, are then assigned so that co-channel or
adjacent channel assignments appear periodically in different
sectors. The primary disadvantage of frequency planning based upon
a reuse grid is that, within a given network, varying terrain and
man-made "clutter", such as buildings and other structures, will
affect the characteristics of radio propagation and attenuation.
Therefore, adhering to a fixed and rigid co-channel or adjacent
channel spacing on a grid will likely provide inadequate isolation
in some cases, resulting in excessive interference, and more than
the required isolation in others, thereby reducing reuse
efficiency. Furthermore, in addition to less than optimal
interference levels, the fixed reuse approach results in much
reduced capacity in many parts of the network where frequencies can
be added freely due to an RF shield, such as a mountain ridge, but
the grid prohibits such an assignment.
[0010] In pixel based interference analysis, the entire network
service area is divided into a large number of very small "pixels"
or "bins". In one example, each pixel would be a 100 meter square,
so that a network service area of 100 kilometers by 100 kilometers
would contain 1 million pixels. For each pixel, a system engineer
will ascertain the strongest incident signal level from the sectors
nearby and then the incident signal levels from each of the other
sectors in the network to determine potential interferences. From
this information, the system engineer can determine the predicted
levels of co-channel or adjacent channel interference that would be
present in that pixel if certain sectors were assigned,
respectively, the same radio channels as the serving sector or
channels adjacent to those in the serving sector.
[0011] However, pixel-by-pixel interference analysis also has many
significant limitations. While pixel by pixel analysis can predict
interference problems that are likely to result from a proposed
frequency plan, it does not provide any such plan in the first
place, nor does it inherently suggest modifications to a frequency
plan that would reduce interference. Furthermore, there is an
inherent limitation on the amount of data that can be presented in
pixel by pixel interference analysis. At the same time, pixel by
pixel analysis produces an amount of data which is not easily
susceptible to human interpretation. Finally, because conventional
pixel by pixel interference analysis relies solely on predicted
levels, it carries over the inaccuracies in such data as described
above and results in erroneous frequency assignments.
[0012] Thus, while these existing techniques can provide for some
measure of protection and relief from channel interference in the
network service area, they still fail to account for the many
variables and factors which can affect wireless communications on a
day to day basis. Accordingly, it would be desirable to have a
system and method for frequency planning within a wireless
communication network which accounts for the many variables and
factors affecting the quality of wireless communications, reduces
the interference experienced during wireless communication, and
does not limit the coverage area of network cells.
SUMMARY OF THE INVENTION
[0013] The present invention provides a system and method for
creating an impact matrix for use in allocating frequency channels
in a wireless communication network service area which is divided
into a plurality of sectors and further divided into a plurality of
pixels. The impact matrix provides impact scores which characterize
the impact of making certain co-channel or adjacent channel
assignment in pairs of sector by sector within a network service
area.
[0014] The impact scores are developed by a series of steps, the
first of which involves selectively merging signal propagation
analysis data and empirical measurement data to determine an
anticipated signal level for each one of the plurality of pixels in
the network area. Once the signal levels within each pixel are
obtained, a determination is made as to which sector within the
network service area is serving that particular pixel. The system
then assigns a weighted channel interference impact score for the
pixel based on the interference between the pixel's signal serving
sector and signals from each of the other non-serving sectors in
the network area. Overall sector by sector impact scores based on
the weighted channel interference impact scores are determined for
all of the pixels for which a sector is the serving sector.
[0015] In one embodiment of the present invention, the signal level
data from the signal propagation analysis, empirical measurement,
and switch logs analysis is merged according to user assigned
confidences for the data. The step of determining a weighted
channel interference impact score between the pixel's signal
serving sector and signals from each of the other sectors in the
network area includes calculating a ratio between a signal level
from the serving sector and signal levels from each of the other
sectors in the network area, assigning interference impact scores
for each of the other sectors in the network area, and adjusting
the interference impact scores according to user assigned factors
such as network area sensitivity to call quality and amount of call
volume for that network area.
[0016] Once the impact matrix is developed, the scores in the
matrix may be modified to further accurately characterize the
signal impacts of interferences within a network service area. The
impact matrix scores may be adjusted according to data which may
have been previously input to the system or may be
contemporaneously input. Such data includes channel pairing
relationships among sectors which are known to provide low levels
of excessive interference, channel pairing relationships among
sectors which are known to provide high levels of excessive
interference, and detailed call history information. Detailed call
history information can include data on dropped calls and
associated sector and channel combination where call drops
occur.
[0017] The impact matrix may then be used for frequency planning in
the network service area. The impact matrix will provide a user,
typically a network engineer, with a way to predict the signal
quality impact of certain channel assignments within the network
service area.
BRIEF DESCRIPTION OF THE DRAWINGS
[0018] FIG. 1 illustrates a wireless communications network service
area which is divided into cells.
[0019] FIG. 2A illustrates a network service area cell of FIG. 1
divided into sectors.
[0020] FIG. 2B is a detailed illustration of portion A in FIG. 2A
showing a sector divided into pixels.
[0021] FIG. 3 illustrates an exemplary impact matrix developed in
accordance with the teachings of the present invention.
[0022] FIG. 4 is a flow chart illustrating a process for
determining interference impact scores for use in developing the
impact matrix.
[0023] FIG. 5 is a flow chart illustrating a process for
determining a signal level within a pixel in the service area.,
[0024] FIG. 6 is a flow chart illustrating a process for
determining the potential interference impact of incident signals
in a pixel from each of the other sectors in the network.
[0025] FIG. 7 illustrates how overall impact scores are determined
for the impact matrix.
[0026] FIG. 8 is a flow chart illustrating a process for modifying
the impact matrix.
[0027] FIG. 9 illustrates a computer system using an impact matrix
of the present invention for frequency channel planning in a
network service area.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0028] Referring to FIG. 1, there is shown a schematic layout of a
wireless communications network service area 10 divided into cells
14. It should be understood that the hexagonal shape of cells 14
depicted in FIG. 1 merely represents a drawing convention. Such a
hexagonal cell representation has been chosen because it approaches
a circular shape that is the ideal power coverage area for a
wireless communications network service cell. Use of such circular
shapes would involve overlapped areas and make a drawing of the
served area unclear. With the hexagonal shaped cell convention, on
the other hand, the plurality of cells representing a service area
can be depicted with no gap and no overlap between cells.
Generally, a typical wireless network would have far more than the
illustrated number of cells but the numbers shown are sufficient
for illustrative purposes.
[0029] As shown in FIG. 1, each cell 14 contains base stations 18
which are located toward the center of each cell 14. Typically the
base stations employ omni-directional antennas, while base stations
located toward a cell boundary typically employ directional
antennas. Operating within a communications service area are
typically a large number of mobile telephone stations, or mobiles
22. At any given point in time, a subset of these mobiles will be
engaged in calls.
[0030] As shown in FIG. 2A, each cell 14 in the wireless
communication network service area may be divided further into
sectors 30 to improve the coverage or maximize the reuse factor
without increasing the interference level of the available
frequency channels. Additionally, as shown in FIG. 2B, the network
service area may be further divided into pixels 40 to assist in
analyzing communication signal quality and interference on a more
detailed basis. Typically, during wireless communications, the
communicating mobile 22 will be assigned a particular frequency
channel in the sector within which the mobile 22 is currently
operating. If the mobile 22 moves from one sector which is
currently servicing the communication, the "serving sector", to
another sector which takes over the servicing of the communication,
the "target sector", a "handoff` occurs in which the mobile 22 is
assigned a new frequency channel from those available in the target
sector.
[0031] In the present invention, the frequency channels correspond
to the frequencies in approximately the 800 MHz band to the 1900
MHz band. The invention is intended for use in a system such as a
Netplan system for the purpose of facilitating frequency planning
for digital and/or analog channels, the invention will work in a
dual mode system where analog and digital frequencies share the
spectrum in each cell. The present invention is applicable to, but
not limited to, "Advanced Mobile Phone System" ("AWS"), "Total
Access Communications System" ("TACS"), "Nordic Mobile Telephone"
("NMT"), "Time Division Multiple Access" as defined by the
Telecommunications Industry Association (TIA) interim standard
IS-136 ("TDMA"), and "Global System for Mobile" ("GSM")
protocols.
[0032] Referring to FIG. 3, the system and method of the present
invention develops and generates an impact matrix 50 for use in
frequency planning for a wireless communication network service
area. Generally, the impact matrix 50 is a representation of the
potential signal quality impact of making certain co-channel or
adjacent channel assignments between two sectors within a wireless
network, such as a cellular telephone network. It is contemplated
that the impact matrix may also be organized by pixel by pixel
and/or a cell by cell rather than sector by sector. In a preferred
embodiment of the present invention, two main matrices are
developed, one which addresses the impact of co-channel
interference and the other which addresses the impact of adjacent
channel interference. The methods and processes shown and described
herein will be applicable to either co-channel or adjacent channel
interference determinations and measurements. In addition, the
impact matrix is independent of the frequencies used in the
wireless system, as long as the system works within a given
interval such as, in one embodiment, a 100 MHz interval. Two impact
matrices would be developed for use in a dual band network.
[0033] In the impact matrix, the columns 54 represent specific
serving sectors in the network service area and the rows 58
represent interfering sectors in the network service area. A sector
is considered to be a serving sector if, at a given point, the
sector is currently providing the communications link to the mobile
unit. The interfering sectors or "non-serving" sectors may be any
sector within the network service area which may cause interference
in the serving sector by virtue of a co-channel or adjacent channel
assignment in that non-serving sector. For example, if a serving
sector, denoted for exemplary purposes as sector S.sub.1 is
assigned a channel X, and one other sector S.sub.2, within the
network service area is also assigned channel X, then sector
S.sub.2 will be considered a potentially interfering sector.
[0034] In a preferred embodiment, the impact matrix will typically
be of the dimension Q by Q, where Q is equal to the number of
sectors in the network. In other embodiments, Q may include some
sectors in neighboring networks which might interfere with, or be
subjected to, interference from sectors that lie near the edge of
the actual network service area under consideration. In such a
case, the impact matrix should still be kept as a square by using
null data in fields representing neighboring networks as serving
sectors.
[0035] Generally, the impact matrix is developed by performing
various signal quality measurements on a set of frequency channels
in a network service area cell and adjusting the signal quality
measurements based on a variety of factors or signal impacts, as
discussed in more detail herein. In an exemplary embodiment, signal
quality measurements are made not only for those frequency channels
in use or available for use, but also for those frequency channels
that are not currently being used or available for use, though they
may become available at a later time. These various signal quality
measurements are processed, filtered, and evaluated, as described
in greater detail below, and used as a basis for changing
assignments of frequency channels.
[0036] The impact matrix 50 contains impact scores 72 which relate,
on a sector by sector basis, the overall quality impact of making
certain channel assignments in certain sectors pairings. Take, for
example, the specific pairing of serving sector S.sub.2 (column
S.sub.2) and interfering sector S.sub.3 (row S.sub.3). An impact
score of "66" is given to the pairing of serving sector S.sub.2 and
interfering sector S.sub.3 in the impact matrix of FIG. 3. The "66"
represents the overall quality impact in areas served by sector
S.sub.2 when a co-channel or adjacent channel assignment is made in
sector S.sub.3 The scores 72 as shown in FIG. 3 are merely
represented on a scale from one to ninety-nine for exemplary
purposes only. It is contemplated that any numeric scale may be
used in developing the impact matrix, such as a one to ten scale or
any other similar scale which can provide for a relative rating in
the matrix. In developing the impact scores, the system and method
of present invention allow multiple data "layers" to be applied and
merged so as to more accurately represent the potential signal
interference impacts between sectors.
[0037] As shown in FIG. 3, in creating the impact matrix of the
present invention, a number of data files or "layers" are used to
provide data for development of the impact matrix. In some
embodiments, such data includes output files from computer RF
propagation analyses 60, output files from empirical measurements
62, files containing or implying lists of co-channel and/or
adjacent channel pairing relationships among various sectors 64,
and files which provide details of call records for the network for
some period of time 66. Other types of data or output files may be
used in accordance with the teachings of the present invention,
where the data may affect the signal quality within the network
service area. The system and method of the present invention are
scalable so that any number of data layers are able to be
incorporated into the overall impact matrix. In the present system,
each of these data types or files constitutes a "layer" for
eventual incorporation into an overall unified impact matrix.
[0038] As shown in FIG. 4, in one embodiment of the present
invention, the development of the impact matrix generally begins
with a determination of signal levels within the network service
area, step 100. Once signal level information is obtained and
calculated, it is determined which sector within the network
service area is the serving sector for a particular pixel, step
104. Once the serving sector is identified, the potential
interference of other sectors on this serving sector is quantified
by way of an interference impact score assigned to that specific
pairing of serving sector and interfering sector, step 108.
Finally, the interference impact scores are adjusted according to
some user inputtable variables and factors, step 112. The steps of
the process shown in FIG. 4 will be now discussed in more detail
below.
[0039] Referring now to FIG. 5, in constructing the impact matrix,
the system of the present invention endeavors to determine the
signal level within each pixel of the network service area. The
process begins with a basic RF propagation analysis for the network
service area, step 120. By way of background, the RF propagation
analysis is typically based on signal predictions which take into
account area topology, antenna heights, transmit power levels and
even extant man-made clutter, such as building, bridges, etc. Such
propagation predictions are most often performed by computer
simulation programs running specially designed RF propagation
analysis software, such as MSI's Plantet, Motorola's Netplan, or
LCC's CellCard. After RF propagation analysis is performed,
empirical measurement data is collected to provide additional
information about signal levels within each pixel in the network
service area, step 124. Collecting empirical signal level
measurements typically are made by a receiver provided either in a
mobile unit, such as car or in a hand held scanner, which scans
discrete channels being transmitted by the various sectors. The
measurement receiver is moved about in the network to collect
signal level data in a large number of pixels, often in the form of
so-called "drive tests".
[0040] Once the propagation analysis and empirical measurements are
completed, confidences may be assigned to the signal level data,
step 128. For example, if it is known that for a certain area the
RF propagation analysis data will be incorrect or skewed, a user
may assign more confidence to the empirical measurement data for
that certain area. Conversely, if it is known that for another
service area, the empirical measurement information is somehow
inaccurate because, for example, of possible physical/environmental
clutter which may affect the empirical readings, then the user may
assign more confidence to the RF propagation analysis information
in that instance.
[0041] In one embodiment, a two-dimensional representation of the
network service area in map format is provided to a user, on which
the user can "draw" such areas as polygons or other arbitrary
shapes using a "mouse" or other pointing device to designate areas
to which to assign confidences to either the propagation or
empirical measurements. The user may also simply assign confidence
ratings to either the propagation analysis or empirical measurement
information. Such ratings may be simply a one to ten rating or any
scale which can rate the data on a relative basis. In such an
example, the signal level data which the user has the most
confidence in will be assigned a "10" and the data which the user
has the least confidence in will be assigned a "1."
[0042] Once confidences are assigned, the system merges propagation
analysis and empirical measurement information, step 132, in
accordance with confidences assigned by the user. In an exemplary
embodiment, the basic logic for the merging of the propagation
analysis data and the empirical measurement data is accomplished
according to the following pseudo-code:
1 for current_point = {points in drive-test} { for freq. = {
frequencies measured in current frequency { for each antenna
transmitting at the current frequency { using some basic RF
prediction model, calculate the predicted signal strength in the
drive test point region (.about.500 m radius), apply a geometric
correlation test to the sampled and predicted measurements. Store
the correlation index. iterate to next antenna } if none of the
antennas satisfied some minimal correlation threshold go to
frequency loop take the antenna with the best correlation index and
declare it as the transmitter of the current frequency at the
current point. iterate to next frequency } iterate to next point
}
[0043] The merging of propagation analysis and empirical
measurement information is done as a preliminary step in
determining which sector in the network service area is serving a
current pixel. This is accomplished by first determining which
antenna in the network service area is transmitting the current
signal being measured at the current pixel (current point). The
process for determining signal levels within a network service area
is basically accomplished by the nested series of loops, as shown
above, whereby readings are taken at a certain point (pixel) within
the network service area, then at each point a certain frequency is
measured, then for that certain frequency, the different antennas
transmitting at that frequency are examined.
[0044] Essentially, a point by point (current_point) frequency
signal analysis is conducted for all the points in the empirical
test (points in drive_test). At each point, frequencies are
measured (frequencies measured in current_point) to determine
viable frequencies at that point. Then, for each antenna
transmitting at the current frequency, the predicted signal
strength is determined using basic RF prediction model data. A
geometric correlation test is applied to the currently empirically
sampled signal measurement and the predicted signal strength
measurement to determine a correlation index. This correlation
index is then stored. This process of determining and storing a
correlation index is repeated for each antenna transmitting at the
current frequency. If none of the antennas satisfy a minimal
correlation threshold, the next frequency at the current point is
examined. This process is then repeated for the next point or pixel
in the empirical measurement analysis.
[0045] Once at least two correlation indices are determined for the
frequency at the current point, the at least two indices are
compared and the antenna with the "best" correlation index is
determined to be the transmitter of the current frequency at the
current point. The "best" correlation index is obtained for the
antenna with the best match between the prediction and sample and
whose complete set of frequencies is measured in a coordinated way.
After this determination is made for the current frequency, the
system iterates to the next frequency and repeats the above process
of determining the transmitter of the frequency.
[0046] Having merged the RF propagation analysis and empirical
measurement data for every pixel in the network service area, the
system now has a signal strength per pixel file in which, for each
pixel in the network, the anticipated incident signal levels from
each sector are retained. Those skilled in the art will appreciate
that typically, in each pixel, the anticipated signal level from
the vast majority of the sectors in the network will be below a
thermal noise floor, and may thus be disregarded. Typically, the
thermal noise floor will be approximately at or below 130 dB.
[0047] Referring back to FIG. 4, the present system and method
identifies, in each pixel, the associated serving sector for that
pixel, step 104. The probability of a mobile being served by a
given antenna at a given point depends in part on the RF
propagation layer, e.g., the signal strength of each antenna at
each point, and also in the logical organization of the network
which takes into account factors such as the handoff regulation
algorithm and parameters. The following pseudo-code demonstrates
the basic logic employed in an exemplary embodiment for determining
which will be the serving sector for a given pixel or point in the
network service area:
2 for current_point = {points in sample} { calc the best server in
current_point. calc the best server signal strength at
current_point. } for current_sector = {sectors in the network} {
for neighbor = {neighbors to current_sector) { flow = number of
times user handoff between current_sector and neighbor. Simulate
user movements and the handoff process (using the specific system
handoff algorithm) and update the service probabilities in non-best
server areas (known as handoff zone). } }
[0048] In an exemplary embodiment, the system determines for the
current pixel (current_point) out of all the pixels in the network
service area (points in sample), the best server for the
current_point and the best server signal strength at the
current_point, as described above. Then for the current sector
(current_sector) out of all the sectors in the network, each
neighboring sector (neighbors to current_sector) is examined based
on the flow, user movements and the handoff process to determine
service probabilities for each of the sectors. The system predicts,
taking into account the system specific handoff algorithm which may
vary between communication systems, which sector will serve a given
pixel based on the handoff performance between the current_sector
and neighboring sectors (neighbors to current_sector.) Thus, a
sector will likely be a serving sector for a given pixel, if the
sector both provides a strong signal to a given pixel and also
actively coordinates handoffs in that given pixel's area.
[0049] Referring back now to FIG. 4, once the system determines
which is the serving sector for each pixel, the system begins with
an analysis of the potential interference impacts between signals
from each of the other non-serving sectors in the network with that
pixel's serving sector, step 108. As shown in FIG. 6, the process
for determining the potential interference impact of signals begins
with determining the carrier-to-interference (C/I) ratios for each
potentially interfering sector, step 140. Typically, these C/I
values are calculated in decibels ("dB"). A large C/I ratio
indicates a signal that is substantially isolated from channel
interference while a small C/I ratio indicates a signal having
substantial channel interference. Thus, large C/I ratio values
between conventional cellular base stations that are, for example,
greater than approximately 18 dB, indicate that such base stations
can use the same channel while small C/I ratio values between base
stations, such as, for example, less than approximately 12 dB,
indicate that substantial interference will probably occur between
those two base stations when using the same or adjacent frequency
channels. The specific C/I values are determined typically by the
type of air interference technology used (GSM Vs TDMA, for example)
and the service parameters the operator may want to use.
[0050] The system of the present invention maintains a user
modifiable table which develops a quality impact "score" with
respect to the determined C/I. For example, in an exemplary
embodiment as shown below in Table 1, the quality impact score will
range from zero to ninety-nine, with zero representing no
perceptible quality impact and ninety-nine representing severe
interference virtually certain to result in a dropped call. In a
more specific example, a score of 0 is assigned for a potential
interferer in pixels where C/I is determined to be above 17 dB and
a score of 99 for a potential interferer in pixels where C/I is
determined to be below 9 dB.
3 TABLE 1 Impact Score C/I (dB) 0 18 50 13 99 8
[0051] As shown in FIG. 6, using the C/I scoring table shown and
described above, the system will then assign an interference impact
score for each potential interfering sector in each pixel in the
network, step 142. Referring again to FIG. 6, these interference
impact scores are then adjusted according to various weighting
factors, step 144.
[0052] In one preferred embodiment, the system uses weighting
factors which are specified by the user. In particular, the system
allows identification of areas within the network service area in
which sensitivity to call quality is particularly high and other
areas where such sensitivity is relatively low. For example, areas
frequented by top government officials may be designated as "high"
sensitivity and low traffic pedestrian areas may be designated as
"low" sensitivity. In this embodiment, the system also allows
identification of specific areas within the network service area in
which peak time call volume, preferably on a per-pixel basis, is
anticipated to be significantly higher than average, and other
specific areas where such anticipated call volume is relatively
low. For example, sections of major highways where vehicular
traffic routinely backs up during "rush hour" might generate much
higher than average peak time call volumes, so the user might
designate such areas as "high" call volume per pixel. "Low" call
volume per pixel designated areas may be locations such as side
roads located in rural townships where activity is minimal. The
user may use a number of different sources of information to
provide such weighting factors, such as traffic reports, call logs
from past activities in certain areas, and consumer feedback
reports which may indicate areas where communication services may
be currently deficient. Once these weighting factors are provided
by the user, the system adjusts the interference impact scores
accordingly, in line with the weighting factors.
[0053] The following pseudo-code demonstrates the basic logic for
determining a single impact score between sectors:
[0054] define the local interferer index function using the tables
matching the current network technology, the tables assigning a
local impact for each co-channel C/I and a potentially different
local impact to each adjacent channel C/I
4 For current_server = {sectors in the network} { for
current_interferer = {sectors in the network ! = current.sub.--
server} { for current_point = {points in which the traffic uses
current server in non zero probability} { compute the C/I of the
current_server and current_interferer at the current_point using
the RF propagation information. compute the cochannel and adjacent
channel local interference indices. } use an integration policy to
collect all the local interference indices to a single impact
between current_server and current_interferer. } }
[0055] In the above pseudo-code, a pixel by pixel analysis is
undertaken for each serving sector (current_server) and each
interfering sector (current_interferer) in the current pixel being
examined. For each pixel (current_point), the C/I is computed for
that specific pixel's serving sector and each of the other
interfering sectors in the network service area (sectors in the
network !=current_server). In one embodiment, the C/I will be
computed using the RF propagation information which may be simple
predicted RF propagation information or alternatively, sampled RF
information and/or the RF information merged with empirical data.
Once the C/I of the current_server and current_interferer is
computed, the co-channel and adjacent channel local interference
indices are computed from the computed C/I at the current_point. In
the present embodiment, the local interference index is a measure
of the user dissatisfaction from experiencing a given C/I in a
given technology. Once the local interference indices are
calculated, the system uses an integration policy to collect or
combine all the local interference indices to generate an impact
score between the current_server and current_interferer for that
given pixel. This combination of local interference indices can be
done using traffic normalized summation, maximization, prioritized
weighted summation, or other variants.
[0056] The system has now created a weighted pixel-by-pixel
characterization of potential interference impacts in the network
service area. From this impact information, the system generates an
impact matrix 146, as shown in FIG. 7. In the impact matrix 146,
each of the columns represents a specific sector in the network
acting as the serving sector. Each of the rows represents a
specific sector in the network acting as an interfering sector.
Thus, an entry in the impact matrix will represent the overall
signal quality impact in areas served by a specific sector which
would be caused by making co-channel or adjacent channel
assignments in another sector. Typically, the higher the score in
the impact matrix, the more of an impact a co-channel or adjacent
channel assignment will have for that specific sector pair.
[0057] To generate an overall impact score for the impact matrix,
the system considers all of the weighted interference impact scores
as determined above for each pixel. In one embodiment, the system
performs a weighted sum integration to generate the impact matrix
from the scores. Referring to FIG. 7, for each sector S.sub.1
S.sub.2, S.sub.3, and S.sub.4. in a network service area, the
system considers all of the pixels for which a specific sector, say
S.sub.1 is the serving sector. For example, if sector S.sub.1 is
the serving sector for pixels P.sub.1, P.sub.2, P.sub.3 and
P.sub.4, then the weighted interference impact scores for pixels
P.sub.1, P.sub.2, P.sub.3 and P.sub.4 are considered in generating
an overall impact score for that sector S.sub.1 and its potentially
interfering sectors, such as S.sub.2, S.sub.3, and S.sub.4. For
example, for each pixel, weighted interference impact scores have
been determined between each pixel serving sector and each of the
other non-serving sectors S.sub.2, S.sub.3, and S.sub.4 (S.sub.1
v.S.sub.2; S.sub.1 v. S.sub.3, S.sub.1 v.S.sub.4). Based on the
weighted interference impact scores, the system determines an
overall impact score for sector S.sub.1 with respect to sectors
S.sub.2, S.sub.3, and S.sub.4. For example, considering sector
S.sub.1 to be the exemplary serving sector and sector S.sub.2 to be
the interfering sector, the system will examine the weighted
interference impact scores for pixels P.sub.1, P.sub.2, P.sub.3 and
P.sub.4 with respect to sector S.sub.2, namely P.sub.1 (S.sub.1
v.S.sub.2), P.sub.2 (S.sub.1 v.S.sub.2), P.sub.3 (S.sub.1
v.S.sub.2) and P.sub.4 (S.sub.1 v.S.sub.2). These weighted
interference impact scores for pixels P.sub.1, P.sub.2, P.sub.3 and
P.sub.4 with respect to sector S.sub.2 are then combined and
weighted to generate an overall impact score for sector S.sub.1 as
the serving sector and sector S.sub.2 as the interfering sector.
This overall impact score will then be placed into the impact
matrix under the column sector S.sub.1 and in the row sector
S.sub.2. The remaining spaces in the impact matrix are populated as
described above. Typically, the spaces in the impact matrix where
the serving sector and the interfering sector are the same sector
remain blank, since the same sector will not be able to interfere
with itself in practice.
[0058] The following pseudo-code demonstrates one set of logic
behind consolidating various layers of information and data into a
single overall impact matrix:
5 input : layers[the_layer] [sector1][sector2] - the impact between
sector1 and sector2 in layer the_layer. weight_from[the_sect]
[layer] : the weight associated to impacts from sector the-sect
with regard to the layer. weight_to[the_sect] [layer] : the weight
associated to impacts to sector the_sect with regard to the layer.
Output : the unified im - im[sector] [sector] for s1 = {set of
sectors} { for s2 = {set of sectors} { im[s1, s2] =
merging_func(s1, s2, {layers[0][s1][s2], layers[1][s1][s2],..}) } }
merging_func(s1,s2, {entry1, entry2,...}) = summ(i, weight_from[s1]
[i] * weight_from[s2] [i] * entry [i])
[0059] In consolidating all the signal and interference data into a
single impact matrix, the system accepts input, such as the
interference impact scores for specific areas (sector1, sector2) of
the network service area, as was determined above. These impact
scores thereby form a "layer" (the_layer) of data for consolidation
into the single impact matrix. Such data may also be weighted, for
example, by specifying which areas within the network service area
are sensitive or are "high" call volume areas. The interference
impact scores and associated weightings are then processed by the
system (merging_func) and outputted into a unified impact
matrix.
[0060] One skilled in the art will recognize that the overall
impact matrix may be generated in many different ways and still
achieve the objectives of the present invention. For example, in a
more general example of an integration technique, arbitrary logical
expression is defined that takes a set of layer values
1M_sect1_sect2_layer_i and an output is generated by applying the
logical expression to the inputs. Having, for example, two input
layers drive_test and heuristic, the system generates the impact
matrix using the following expression:
[0061] If (heuristic>0)
[0062] return heuristic
[0063] else
[0064] return drive_test
[0065] Further embodiments involving combinations of logical
expressions and weighted sums are available, as will be understood
by those skilled in the art after reviewing this description.
[0066] Referring now to FIG. 8, once the impact matrix is
generated, step 150, the impact scores may be adjusted to further
accurately represent potential impacts of channel assignments. The
scores may be adjusted according to the data which defines sector
pairs for which it is known that channel assignment, either
co-channel or adjacent channel, will not result in excessive
interference, step 152. If the impact scores in the impact matrix
suggest interference impacts higher than the known levels, step
154, the scores in the matrix are reduced accordingly, step
156.
[0067] The impact scores may also be modified in accordance to data
which defines sector pairs for which it is known that channel
assignment, either co-channel or adjacent channel, will result in
excessive interference, step 158. If the impact scores in the
impact matrix suggest interference impacts lower than the known
levels, the scores in the matrix are increased accordingly.
[0068] Additionally, the system may adjust the scores in the impact
matrix based on data input which contains call detail information,
such as information which correlates incidences of dropped calls
operating on a given radio channel in a given sector with
simultaneous use of the same (or adjacent) radio channel in another
sector, step 164. When a high correlation of these factors is
found, it is assumed that there is a causal relationship in that
the dropped calls in one sector are likely caused by interference
from the other sector. In this case, the system examines the
corresponding impact score in the impact matrix, step 166. If this
score is not already appropriately high, it is then increased to a
high value, step 168.
[0069] Typically, the system will accept the following inputs prior
to the creation of the impact matrix: files containing or implying
lists of co-channel and/or adjacent channel pairing relationships
among various sectors which are known to provide low levels of
excessive interference; files containing or implying lists of
co-channel and/or adjacent channel pairing relationships among
various sectors which are known to provide high levels of excessive
interference; files which provide details of call records for the
network for some period of time including: for each incidence of a
dropped call: the precise time of the call drop; the RF channel in
use by the call when the drop occurred; and the serving sector of
the call when the drop occurred; for each call handled during the
period covered by the data: the time the call began; the initial RF
channel assigned; the initial serving sector; the time, target
sector, and new RF channel assignment for each handoff; and the
time the call ended.
[0070] In a typical cellular communication network, call detail
information as discussed above may be extracted from switches
within the network communications system which maintain log files
that track various attributes, such as dropped calls, severe C/I
events, up-link noise, failed handoffs and other related events.
Call detail information may also be extracted from performance
monitoring systems such as WantMark's Flex-PM, ADC's Metrica, and
MSI's MAXXER.
[0071] Once modifications to the impact matrix, as described above,
are complete, the impact matrix is used to assist the system
engineer in designing and optimizing a frequency plan for the
network, wherein the object is to assign channels to each cell or
sector in the numbers required while keeping the total quality
impact associated with these assignments to the lowest possible
value.
[0072] As shown in FIG. 9, the methods and systems of the present
invention may be incorporated in software stored on a computer
usable medium such as a hard or floppy disk, CD-ROM, or other
electrical, magnetic, or optical memory device adapted for use on a
computer system 200. Additionally, the methods or systems may also
be incorporated in hardware elements such as specially designed
integrated circuits, as is known in the art. The computer system
200 may provide for the calculation, processing and generation of
an impact matrix 210 in accordance with the teachings of the
present invention. The impact matrix 210 may be used for frequency
planning within a network service area 220 made up of cells or
sectors 230. The impact matrix 210 would provide guidance on how to
make specific channel assignment 240 and/or channel set assignments
250 within each cell or sector 230. For example, if a user desired
to change an existing channel assignment within the network service
area 220, the user would consult the impact matrix 210 to determine
the impact of changing the channel assignment.
[0073] In other embodiments, the system would "score" a given
frequency plan, or a given modification thereto, by applying the
impact matrix's scores to the individual channel assignments in the
plan or modification. For example, if a system engineer needs to
add an RF channel to a particular sector to accommodate growth in
peak call volume, he or she can consider a particular channel
assignment. The impact matrix will provide the incremental quality
degradation that such an assignment will cause within that sector's
service area and in the service areas of each co-channel or
adjacent channel sector.
[0074] While the invention has been described and illustrated in
connection with preferred embodiments, many variations and
modifications as will be evident to those skilled in this art may
be made without departing from the spirit and scope of the
invention, and the invention as set forth in the appended claims is
thus not to be limited to the precise details of methodology or
construction set forth above as such variations and modification
are intended to be included within the scope of the appended
claims.
* * * * *