METHODS OF DETERMINING COVERAGE AREAS
BACKGROUND
A wireless network generally is divided into multiple cells with each
cell having at least one base station. A user equipment (e.g., mobile
phone) wishing to send information establishes communication with a
base station in the cell.
Operating parameters, in addition to identification parameters, are
part of network management. A variety of operating parameters such
as antenna orientation (e.g., tilt angle), transmit power limits and pilot
power fraction affect network function.
In third generation (3G) standards for wireless networks such as
CMDA2000 and Universal Mobile Telecommunications System
(UMTS), performance analysis is used to evaluate general behavior of
network algorithms. For performance analysis in 3G, such as analysis
of handoffs, access performance and application throughput,
hexagonal network models of coverage areas are used.
FIG. 1 illustrates a conventional hexagonal network model. FIG. 1
shows a conventional hexagonal network model 100. As shown, the
hexagonal network model 100 includes base stations BS1-BS7, with
each of the base stations BS1-BS7 having a coverage area C1-C7. As
shown, the coverage areas C1-C7 are cells for the base stations BSi-
BS7 and are modeled as hexagons. Hexagonal network models are
sufficient for 3G technologies.
Long Term Evolution (LTE) is the name given to a project to improve
the Universal Mobile Telecommunications System (UMTS) standard to
cope with future requirements. In one aspect, UMTS has been
modified to provide for the Evolved Universal Terrestrial Radio Access
Network (E-UTRAN) as a fourth generation (4G) wireless network.
An E-UTRAN includes evolved NodeBs (eNodeBs), which provide the
Evolved Universal Terrestrial Radio Access (E-UTRA) user plane
(PDCP/RLC/MAC/PHY) and control plane (RRC) protocol terminations
with a UE. As discussed herein, eNodeB refers to a base station that
provides radio access to user equipments (UEs) within a given
coverage area. This coverage area is referred to as a footprint of a cell.
The eNodeBs are interconnected with each other by an X2 interface.
The eNodeBs are also connected to a Mobility Management Entity
(MME) via an Sl-MME interface (control plane), and to a Serving
Gateway (SGW) via an Sl-U interface (user/ data plane).
In 4G, performance has become more personal and localized with Self-
Organizing and Self-Optimizing Networks (SON). Therefore,
performance analysis evaluation has a greater sense of accountability
and needs to answer specific questions about specific cells.
Consequently, general analysis of networks using hexagonal models is
insufficient. Furthermore, since performance optimization is part of
the network, the analysis and models should provide computational
efficiency to allow these computations to be made on network
elements.
SUMMARY
At least one example embodiment discloses a method of determining
coverage areas in a communication system. The method includes
determining, by a controller, a plurality of base stations in the
communication system and determining, by the controller, a Voronoi
region for each of the plurality of base stations. The Voronoi region
corresponds to the coverage area for the base station.
At least another example embodiment discloses a method of analyzing
performance of a communication system. The method includes
determining, by a base station including at least one antenna, at least
one vertex of a Voronoi region. The Voronoi region corresponds to a
coverage area for the base station and the at least one vertex
corresponds to a maximum transmitting distance.
BRIEF DESCRIPTION OF THE DRAWINGS
Example embodiments will be more clearly understood from the
following detailed description taken in conjunction with the
accompanying drawings. FIGS. 1-6 represent non-limiting, example
embodiments as described herein.
FIG. 1 illustrates a conventional hexagonal network model;
FIG. 2 shows a portion of a communication system according to
example embodiments;
FIG. 3 illustrates a method of determining coverage areas in a
communication system according to example embodiments;
FIG. 4 illustrates a method of determining transmit power based on a
Voronoi region according to example embodiments;
FIG. 5 illustrates a method of determining a tilt angle for an antenna
based on a Voronoi region according to example embodiments; and
FIG. 6 illustrates a communication system having a plurality of
eNodeBs and Voronoi regions according to example embodiments.
DETAILED DESCRIPTION
Various example embodiments will now be described more fully with
reference to the accompanying drawings in which some example
embodiments are illustrated. In the drawings, the thicknesses of
layers and regions may be exaggerated for clarity.
Accordingly, while example embodiments are capable of various
modifications and alternative forms, embodiments thereof are shown
by way of example in the drawings and will herein be described in
detail. It should be understood, however, that there is no intent to
limit example embodiments to the particular forms disclosed, but on
the contrary, example embodiments are to cover all modifications,
equivalents, and alternatives falling within the scope of the claims.
Like numbers refer to like elements throughout the description of the
figures.
It will be understood that, although the terms first, second, etc. may
be used herein to describe various elements, these elements should
not be limited by these terms. These terms are only used to
distinguish one element from another. For example, a first element
could be termed a second element, and, similarly, a second element
could be termed a first element, without departing from the scope of
example embodiments. As used herein, the term "and/or" includes
any and all combinations of one or more of the associated listed items.
The terminology used herein is for the purpose of describing particular
embodiments only and is not intended to be limiting of example
embodiments. As used herein, the singular forms "a," "an" and "the"
are intended to include the plural forms as well, unless the context
clearly indicates otherwise. It will be further understood that the
terms "comprises," "comprising," "includes" and/ or "including," when
used herein, specify the presence of stated features, integers, steps,
operations, elements and/ or components, but do not preclude the
presence or addition of one or more other features, integers, steps,
operations, elements, components and/ or groups thereof.
It should also be noted that in some alternative implementations, the
functions/ acts noted may occur out of the order noted in the figures.
For example, two figures shown in succession may in fact be executed
substantially concurrently or may sometimes be executed in the
reverse order, depending upon the functionality/ acts involved.
Unless otherwise defined, all terms (including technical and scientific
terms) used herein have the same meaning as commonly understood
by one of ordinary skill in the art to which example embodiments
belong. It will be further understood that terms, e.g., those defined in
commonly used dictionaries, should be interpreted as having a
meaning that is consistent with their meaning in the context of the
relevant art and will not be interpreted in an idealized or overly formal
sense unless expressly so defined herein.
An algorithm, as the term is used here, and as it is used generally, is
conceived to be a self-consistent sequence of steps leading to a desired
result. The steps are those requiring physical manipulations of
physical quantities. Usually, though not necessarily, these quantities
take the form of optical, electrical, or magnetic signals capable of
being stored, transferred, combined, compared, and otherwise
manipulated. It has proven convenient at times, principally for
reasons of common usage, to refer to these signals as bits, values,
elements, symbols, characters, terms, numbers, or the like.
In the following description, illustrative embodiments will be described
with reference to acts and symbolic representations of operations (e.g.,
in the form of flowcharts) that may be implemented as program
modules or functional processes including routines, programs,
objects, components, data structures, etc., that perform particular
tasks or implement particular abstract data types and may be
implemented using existing hardware at existing network elements or
control nodes (e.g., a scheduler located at a cell site, base station or
Node B).
Unless specifically stated otherwise, or as is apparent from the
discussion, terms such as "processing" or "computing" or "calculating"
or "determining" or "displaying" or the like, refer to the action and
processes of a computer system, or similar electronic computing
device, that manipulates and transforms data represented as physical,
electronic quantities within the computer system's registers and
memories into other data similarly represented as physical quantities
within the computer system memories or registers or other such
information storage, transmission or display devices.
As used herein, the term "user equipment" (UE) may be synonymous
to a mobile user, mobile station, mobile terminal, user, subscriber,
wireless terminal and/ or remote station and may describe a remote
user of wireless resources in a wireless communication network.
The term "evolved NodeB" may be understood as a one or more cell
sites, Node Bs, base stations, access points, and/or any terminus of
radio frequency communication. Example embodiments described
hereafter may generally be applicable to network architectures, such
as LTE, ad hoc and/or mesh network architectures, for example.
Voronoi tessellations are well known in mathematics. A Voronoi
tessellation includes a plurality of Voronoi regions. Each Voronoi
region includes a generating point. Each point within the Voronoi
region is closer to the generating point for the Voronoi region than any
other generating points for the other Voronoi regions. Segments
(boundary lines) for the Voronoi region are all the points that are
equidistant to the generating point for the Voronoi region and a
generating point for another Voronoi region.
Example embodiments disclose determining a Voronoi region for each
eNodeB (base station) within a communication system. The
determined Voronoi region for each eNodeB is used by a controller of
the communication system as the coverage area for the eNodeB. The
eNodeB is the generating point for the Voronoi region. Since the
coverage areas are based on associated Voronoi regions, all locations
within a coverage area are closest to the eNodeB associated with the
coverage area.
FIG. 2 shows a portion of an E-UTRAN deployment including a
network management layer 200 in communication with a plurality of
eNodeBs 205. As is well-known, multiple cells or a single cell are
often associated with a single eNodeB.
The E-UTRAN network management layer 200 includes a Mobility
Management Entity (MME) 2 10 and a serving gateway SGW 2 12. The
MME 2 10 is a logical entity that controls the eNodeBs 205 and
coordinates scheduling and transmission for eNodeBs 205. In more
detail, functions of the MME 2 10 include scheduling and timing
control, eNodeB registration and feedback. The MME 2 10 is in twoway
communication with the eNodeBs 205. As described in 3GPP TS
36.300 V.8.6.0, the entire contents of which is incorporated herein by
reference, the MME 2 10 controls, inter alia, user radio access network
(RAN) mobility management procedures and user session management
procedures.
For example, the MME 10 controls a UE's tracking and reachability.
The MME 2 10 also controls and executes transmission and/or
retransmission of signaling messages such as paging messages for
notifying destination UEs of impending connection requests (e.g.,
when UEs are being called or when network initiated data intended for
the UE is coming).
The SGW 2 12 is a data plane element. The SGW 2 12 is a mobility
anchor during handoffs between eNodeBs 205 and an anchor for
mobility between LTE and other 3GPP technologies.
While example embodiments are described with reference to a 4G/LTE
network, example embodiments are contemplated as being applicable
to any wireless communication infrastructure.
FIG. 3 illustrates a method of determining coverage areas in a
communication system. The method of FIG. 3 may be performed by a
controller in a network management layer such as the MME 2 10 in
the network management layer 200. More specifically, a controller
that implements the method of FIG. 3 determines a plurality of base
stations in the communication system and determines a Voronoi
region for each of the plurality of eNodeBs. The Voronoi region
corresponds to the coverage area for the eNodeB.
At step S300, the controller determines a number of a plurality of
eNodeBs (base stations) in the communication system. The controller
may determine the number of eNodeBs by any known method. The
controller may set a limit of the number of eNodeBs.
At step S3 10, the controller then determines a Voronoi region (cell
footprint) for each of the plurality of eNodeBs. More specifically, the
controller determines a Voronoi tessellation, including the Voronoi
regions, for the cell sites in the communication system (e.g., a radio
access network). The controller determines a Voronoi region by using
an associated eNodeB as a generating point for the Voronoi region.
Algorithms used to determine Voronoi tessellations are known in fields
not related to communications. However, the controller may use any
known algorithm used to determine the Voronoi tessellation and the
Voronoi regions within the Voronoi tessellation.
For example, the controller may assume a flat-world view to determine
the Voronoi regions. The controller may use Fortune's Algorithm to
determine the Voronoi regions for the eNodeBs using the locations of
the eNodeBs (e.g., x and y coordinates) in Fortune's Algorithm.
Once the controller determines the Voronoi tessellation, the controller
sets the coverage areas for the eNodeBs based on the associated
Voronoi regions, respectively, at step S320. The coverage area used
for performance analysis for an eNodeB is the associated Voronoi
region for the eNodeB. Since the coverage areas are based on the
associated Voronoi regions, all locations within a coverage area are
closest to the eNodeB associated with the coverage area.
The controller is configured to transmit a signal indicating an
associated Voronoi region to each eNodeB. Moreover, each eNodeB
sets initial parameter values based on the associated Voronoi region.
For example, the controller may assume a flat-world view and
determine the Voronoi regions based on the flat world-view. Using the
Voronoi regions, the controller determines the initial parameter
values. The initial parameter values are populated in each cell and
refined based on UE measurements. The initial parameter values may
include signal power, power offsets for traffic and control channels,
antenna tilt angles, handoff parameters and reselection parameters.
As such, in performance analysis, the coverage area for an eNodeB is
not a hexagon. By contrast, the coverage area according to example
embodiments is a convex polygon (Voronoi region) .
Because of the nature radio propagation (receive level decreases
according to distance from transmitter), Voronoi regions provide many
benefits over the conventional hexagonal model.
Two such examples are antenna tilt and transmit power. The
transmit power of an eNodeB is associated with one of the vertices of
the Voronoi region.
FIG. 4 illustrates a method of determining transmit power based on a
Voronoi region. FIG. 5 illustrates a method of determining a tilt angle
for an antenna on an eNodeB based on a Voronoi region. FIG. 6
illustrates a communication system having a plurality of eNodeBs and
Voronoi regions as coverage areas. FIG. 6 is used to describe the
methods illustrated in FIGS. 4 and 5. The methods illustrated in
FIGS. 4 and 5 may be implemented by an eNodeB in a communication
system such as the eNodeBs 205 shown in FIG. 2.
FIGS. 4 and 5 are implemented by an eNodeB in communication with
a controller that is configured to determine Voronoi regions for
coverage areas. The eNodeB includes at least one antenna.
At step S400, the eNodeB determines the associated Voronoi region for
the eNodeB. More specifically, the eNodeB receives a signal indicating
the Voronoi region from the controller. Using FIG. 2 as an example,
the eNodeB receives a signal indicating the Voronoi region from the
MME 2 10. The eNodeB also determines at least one vertex (e.g., a
vertex farthest from the location of the eNodeB) of the associated
Voronoi region. The at least one vertex may be a maximum distance
dmax within the associated Voronoi region from the eNodeB.
The eNodeB then determines a transmit power for the coverage area
based on the maximum distance dm ax , at step S4 10. The transmit
power is determined by the eNodeB so that every UE within the
coverage area (Voronoi region) may receive signals transmitted by the
eNodeB. At step S420, the eNodeB transmits signals at the transmit
power to UEs within the coverage area for the eNodeB.
As described, the eNodeB first determines at least one vertex of a
Voronoi region. The Voronoi region corresponds to a coverage area for
the eNodeB and the at least one vertex corresponds to a maximum
transmitting distance. Consequently, the eNodeB receives the
determined Voronoi region from the controller.
FIG. 5 illustrates a method of determining a tilt angle for an antenna
based on a Voronoi region. Step S500 is the same as step S400.
Therefore, a detailed description of step S500 is not provided, for the
sake of brevity.
At step S5 10, the eNodeB determines a tilt angle for the antenna
based on the maximum distance dm ax and a height of the antenna h .
The determination of the tilt angle is described in more detail with
reference to FIG. 6.
Once the eNodeB determines the tilt angle of the antenna, the eNodeB
transmits signals at the tilt angle at step S520. While the eNodeB
described includes one antenna, it should be understood that example
embodiments may include eNodeBs having multiple antennas. For
example, example embodiments may be implemented in a multiple
input-multiple output (MIMO) system.
Each of FIGS. 3-5 may be performed by the controller and eNodeBs
every time the controller detects that an eNodeB becomes inactive
(e.g., shuts down) or is added to the communication system, for
example. If an eNodeB goes down, the controller reconfigures the
Voronoi regions for each active eNodeB. Therefore, the coverage areas
for the active eNodeBs would compensate for the lost coverage area
due to the eNodeB that is inactive.
FIG. 6 illustrates a communication system having a plurality of
eNodeBs and Voronoi regions as coverage areas. As shown, a
communication system 600 includes eNodeBs ENi-ENio. Each
eNodeB ENi-ENio is associated with a coverage area CAi-CAio. While
not shown, it should be understood that the communication system
600 includes a controller like the MME 10. The controller
determines the coverage areas CAi-CAio, as described in the method
of FIG. 3.
For the sake of clarity and brevity, the eNodeB ENi and the coverage
area CAi for the eNodeB ENi is described. However, it should be
understood that the description of the eNodeB ENi is applicable to the
eNodeBs EN2-EN10. Moreover, while the communication system 600 is
illustrated as having ten eNodeBs, the communication system 600
may include more or less than ten eNodeBs and example
embodiments should not be construed as being limited to ten
eNodeBs.
As shown, the eNodeB ENi includes an antenna Ai configured to
transmit and receive signals to/from UEs in the coverage area CAi
and to/from the controller. The antenna Ai is located at a height h
above ground.
Based on a signal received from the controller, the eNodeB ENi
determines the vertices of its associated Voronoi region (step
S400/S500), the coverage area CAi. The Voronoi region for the
coverage area CA includes vertices V1-V5 . As shown, the vertex V5 is
the maximum distance dmax from the eNodeB EN . Since the transmit
power that is determined by eNodeB EN is based on the maximum
distance dm ax from the eNodeB EN to an edge of the coverage area
CA , each UE within the coverage CA receives signals transmitted by
the eNodeB EN at the transmit power.
The eNodeB EN determines the transmit power using the following
equation:
= ( )
wherein P is a power receive level at a point at the distance dmax from
the eNodeB EN . A transmit power for the eNodeB EN is To and a is
an attenuation constant based on the frequency band of operation.
The coverage area CA also includes points S1-S3 that are determined
by the eNodeB EN based on a sector configuration for the ENodeB
Moreover, the eNodeB EN determines the antenna tilt a s follows:
Once a UE communicates with the eNodeB EN , actual UE
measurements may provide a more accurate estimate of the maximum
path loss than the maximum path loss based on the attenuation
constant a . The difference between maximum path loss based on the
attenuation constant a and the maximum path loss based on the UE
measurements is used by the eNodeB EN to update transmit-power
compensation powers, a s well a s load-balancing power estimates.
Example embodiments are described with each base station/ eNodeB
covering an Omni cell, for the sake of convenience. However, example
embodiments may be extended to any number of sectors/ cell.
Example embodiments being thus described, it will be obvious that
the same may be varied in many ways. Such variations are not to be
regarded as a departure from the spirit and scope of example
embodiments, and all such modifications as would be obvious to one
skilled in the art are intended to be included within the scope of the
claims.
CLAIMS
What is claimed is:
1. A method of determining coverage areas in a communication
system, the method comprising:
first determining (S300), by a controller, a plurality of base
stations in the communication system, the controller being configured
to communicate with the plurality of base stations; and
second determining (S3 10), by the controller, a Voronoi region
for each of the plurality of base stations, the Voronoi region
corresponding to the coverage area for the base station and each
location in the Voronoi region is closest to the base station than any
other base station of the plurality of base stations.
2. The method of claim 1, wherein the first (S300) and second (S3 10)
determining are performed if the controller detects another base
station in the communication system or if the controller cannot not
communicate with one of the plurality of base stations.
3. The method of claim 1, wherein the second determining (S3 10)
determines the Voronoi region based on the base station being a
generating point of the Voronoi region.
4. The method of claim 1, wherein the second determining (S3 10)
determines the Voronoi region for each of the plurality of base
stations, the Voronoi regions not overlapping.
5. A method of analyzing performance of a communication system,
the method comprising:
determining (S400), by a first base station including at least one
antenna, at least one vertex of a Voronoi region, the Voronoi region
corresponding to a coverage area for the base station, each location in
the Voronoi region is closest to the base station than any other base
stations, and the at least one vertex corresponding to a maximum
transmitting distance.
6. The method of claim 5, further comprising:
second determining (S4 10), by the first base station, a transmit
power based on the at least one vertex of the Voronoi region.
7. The method of claim 6, further comprising:
transmitting (S420), by the first base station, a pilot signal at
the transmit power.
8. The method of claim 6, wherein the second determining (S4 10)
determines the transmit power further based on a path loss threshold.
9. The method of claim 6, further comprising:
third determining (S5 10), by the first base station, a tilt angle
for the at least one antenna based on the at least one vertex of the
Voronoi region.
10. The method of claim 9, further comprising:
transmitting (S520), by the first base station, a pilot signal at
the tilt angle.