U.S. patent application number 13/864860 was filed with the patent office on 2013-09-05 for method and apparatus for cooperation strategy selection in a wireless communication system.
This patent application is currently assigned to QUALCOMM Incorporated. The applicant listed for this patent is QUALCOMM INCORPORATED. Invention is credited to Alan Barbieri, Alexei Y. Gorokhov, Jilei Hou, Siddhartha Mallik.
Application Number | 20130229935 13/864860 |
Document ID | / |
Family ID | 42074243 |
Filed Date | 2013-09-05 |
United States Patent
Application |
20130229935 |
Kind Code |
A1 |
Gorokhov; Alexei Y. ; et
al. |
September 5, 2013 |
METHOD AND APPARATUS FOR COOPERATION STRATEGY SELECTION IN A
WIRELESS COMMUNICATION SYSTEM
Abstract
Systems and methodologies are described that facilitate
cooperation strategy selection for a network
multiple-in-multiple-out (N-MIMO) communication system. As
described herein, one or more nodes in a communication system
capable of N-MIMO communication can calculate marginal utilities,
projected per-user rates, and/or other parameters corresponding to
respective associated users. Based on these calculations,
respective network nodes can perform user scheduling and selection,
cell scheduling and selection, selection of a cooperation strategy
(e.g., coordinated silencing, joint transmission, coordinated
beamforming, etc.), and/or other operations to provide cooperative
communication for respective users. As further described herein,
projected rate calculation for a given user can be adjusted based
on processing or channel implementation loss associated with the
user, interference nulling capability of the user, or other
factors. As additionally described herein, these and/or other
parameters can be fed back by respective users to a serving network
node and/or mandated via system performance requirements.
Inventors: |
Gorokhov; Alexei Y.; (San
Diego, CA) ; Mallik; Siddhartha; (San Diego, CA)
; Barbieri; Alan; (San Diego, CA) ; Hou;
Jilei; (Carlsbad, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
QUALCOMM INCORPORATED |
San Diego |
CA |
US |
|
|
Assignee: |
QUALCOMM Incorporated
San Diego
CA
|
Family ID: |
42074243 |
Appl. No.: |
13/864860 |
Filed: |
April 17, 2013 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
12568269 |
Sep 28, 2009 |
8432821 |
|
|
13864860 |
|
|
|
|
61102282 |
Oct 2, 2008 |
|
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Current U.S.
Class: |
370/252 |
Current CPC
Class: |
H04L 5/0035 20130101;
H04L 5/0073 20130101; H04L 5/0091 20130101; H04W 24/02 20130101;
H04L 5/006 20130101; H04L 5/0023 20130101 |
Class at
Publication: |
370/252 |
International
Class: |
H04W 24/02 20060101
H04W024/02 |
Claims
1. A method, comprising: identifying an amount of processing loss
incurred in communication with at least one associated base
station; and reporting the amount of processing loss as feedback to
the at least one associated base station.
2. The method of claim 1, wherein the identifying comprises
identifying the amount of processing loss according to a channel
implementation utilized for communication with the at least one
associated base station.
3. The method of claim 1, wherein the identifying comprises
identifying the amount of processing loss according to a soft
decoding technique utilized for communication with the at least one
associated base station.
4. The method of claim 1, further comprising obtaining information
relating to a mandated processing loss limit, wherein the
identifying comprises identifying the amount of processing loss
based at least in part on the mandated processing loss limit
5. The method of claim 4, wherein the mandated processing loss
limit is given within a minimum performance specification
(MPS).
6. The method of claim 4, wherein the obtaining information
relating to a mandated processing loss limit comprises: identifying
an associated user equipment (UE) category; and obtaining
information relating to a mandated processing loss limit
corresponding to the associated UE category.
7. A wireless communications apparatus, comprising: a memory that
stores data relating to at least one serving network node; and a
processor configured to determine a processing loss associated with
communication to the at least one serving network node and to
report the processing loss as feedback to the at least one serving
network node.
8. The wireless communications apparatus of claim 7, wherein the
processor is further configured to determine the processing loss
based on at least one of a channel implementation or a soft
decoding technique utilized for communication with the at least one
serving network node.
9. The wireless communications apparatus of claim 7, wherein: the
memory further stores data relating to a maximum processing loss;
and the processor is further configured to determine the processing
loss based at least in part on the maximum processing loss.
10. The wireless communications apparatus of claim 9, wherein the
processor is further configured to identify the maximum processing
loss within a minimum performance specification (MPS).
11. An apparatus, comprising: means for identifying feedback
information relating to device implementation loss associated with
the apparatus; and means for submitting the feedback information to
one or more serving base stations.
12. The apparatus of claim 11, wherein the means for identifying
comprises means for identifying a device implementation loss
associated with the apparatus based on at least one of a channel
implementation or a soft decoding technique utilized for
communication between the apparatus and the one or more serving
base stations.
13. The apparatus of claim 11, further comprising means for
identifying a maximum device implementation loss, wherein the means
for identifying feedback information comprises means for
identifying a device implementation loss associated with the
apparatus based at least in part on the maximum device
implementation loss.
14. The apparatus of claim 13, wherein the maximum device
implementation loss is given within a minimum performance
specification (MPS).
15. A computer program product, comprising: a computer-readable
medium, comprising: code for causing a computer to identify at
least one serving network node; code for causing a computer to
determine a processing loss associated with communication to the at
least one serving network node; and code for causing a computer to
report the processing loss as feedback to the at least one serving
network node.
16. The computer program product of claim 15, wherein the code for
causing a computer to determine a processing loss comprises code
for causing a computer to determine processing loss based on at
least one of a channel implementation or a soft decoding technique
utilized for communication with the at least one serving network
node.
17. The computer program product of claim 15, wherein: the
computer-readable medium further comprises code for causing a
computer to identify a maximum processing loss; and the code for
causing a computer to determine a processing loss comprises code
for causing a computer to determine processing loss based at least
in part on the maximum processing loss.
18. A method, comprising: identifying information relating to an
extent of interference nulling capability of an associated
receiver; and reporting identified information relating to the
extent of interference nulling capability of the associated
receiver to at least one serving network node.
19. The method of claim 18, wherein the identifying comprises
identifying an extent of interference nulling capability of the
receiver based at least in part on a number of antennas associated
with the receiver.
20. The method of claim 18, further comprising obtaining
information relating to a minimum interference nulling requirement,
wherein the identifying comprises identifying an extent of
interference nulling capability of the receiver based at least in
part on the minimum interference nulling requirement.
21. The method of claim 20, wherein the minimum interference
nulling requirement is provided within a set of network-wide
mandated performance parameters.
22. The method of claim 20, wherein the obtaining information
relating to a minimum interference nulling requirement comprises:
identifying an associated user category; and obtaining information
relating to a minimum interference nulling requirement
corresponding to the associated user category.
23. The method of claim 20, wherein the obtaining information
relating to a minimum interference nulling requirement comprises:
identifying a number of supportable simultaneous
multiple-in-multiple-out (MIMO) streams; and obtaining information
relating to a minimum number of dominant interferers for which
nulling is mandated as a function of the number of supportable
simultaneous MIMO streams.
24. The method of claim 20, wherein the obtaining comprises:
identifying a set of interference nulling requirements
corresponding to respective device capability levels, the device
capability levels defined in terms of one or more of number of
receive antennas or multiple-in-multiple-out (MIMO) communication
capability; identifying an associated device capability level; and
selecting an interference nulling requirement from the set of
interference nulling requirements corresponding to the identified
associated device capability level.
25. A wireless communications apparatus, comprising: a memory that
stores data relating to at least one serving network node; and a
processor configured to generate an indicator of interference
nulling capability of a receiver associated with the wireless
communications apparatus and to report the indicator as feedback to
the at least one serving network node.
26. The wireless communications apparatus of claim 25, wherein the
processor is further configured to identify a level of interference
nulling capability corresponding to the indicator based at least in
part on a number of antennas associated with the receiver.
27. The wireless communications apparatus of claim 25, wherein: the
memory further stores data relating to a minimum level of
interference nulling capability for the wireless communications
apparatus; and the processor is further configured to identify a
level of interference nulling capability corresponding to the
indicator based at least in part on the minimum level of
interference nulling capability.
28. The wireless communications apparatus of claim 27, wherein the
processor is further configured to identify the minimum level of
interference nulling capability at least in part by identifying a
number of supportable simultaneous multiple-in-multiple-out (MIMO)
streams and selecting a minimum number of dominant interferers to
be nulled as a function of the number of supportable simultaneous
MIMO streams.
29. An apparatus, comprising: means for identifying feedback
information relating to receiver nulling capability of the
apparatus; and means for submitting the feedback information to one
or more serving base stations.
30. The apparatus of claim 29, wherein the means for identifying
comprises means for identifying receiver nulling capability of the
apparatus based at least in part on a number of receive antennas
associated with the apparatus.
31. The apparatus of claim 29, further comprising means for
obtaining information relating to a minimum required receiver
nulling capability level, wherein the means for identifying
comprises means for identifying receiver nulling capability of the
apparatus based at least in part on the minimum required receiver
nulling capability level.
32. A computer program product, comprising: a computer-readable
medium, comprising: code for causing a computer to identify at
least one serving network node; code for causing a computer to
generate an indicator of interference nulling capability of a
receiver associated with the apparatus; and code for causing a
computer to report the indicator as feedback to the at least one
serving network node.
33. The computer program product of claim 32, wherein the code for
causing a computer to generate comprises code for causing a
computer to identify a level of interference nulling capability
corresponding to the indicator based at least in part on a number
of antennas associated with the receiver.
34. The computer program product of claim 32, wherein the code for
causing a computer to generate comprises: code for causing a
computer to identify a minimum level of interference nulling
capability for the apparatus; and code for causing a computer to
identify a level of interference nulling capability corresponding
to the indicator based at least in part on the minimum level of
interference nulling capability.
Description
CROSS-REFERENCE
[0001] This application is a divisional of U.S. Non-Provisional
Application Ser. No. 12/568,269, filed Sep. 28, 2009, and entitled
"METHOD AND APPARATUS FOR COOPERATION STRATEGY SELECTION IN A
WIRELESS COMMUNICATION SYSTEM", which claims the benefit of U.S.
Provisional Application Ser. No. 61/102,282, filed Oct. 2, 2008,
and entitled "COOPERATION STRATEGY SELECTION IN NETWORK MIMO
SYSTEMS," the entirety of which are incorporated herein by
reference.
BACKGROUND
[0002] I. Field
[0003] The present disclosure relates generally to wireless
communications, and more specifically to techniques for managing
cooperative use of respective entities in a wireless communication
environment.
[0004] II. Background
[0005] Wireless communication systems are widely deployed to
provide various communication services; for instance, voice, video,
packet data, broadcast, and messaging services can be provided via
such wireless communication systems. These systems can be
multiple-access systems that are capable of supporting
communication for multiple terminals by sharing available system
resources. Examples of such multiple-access systems include Code
Division Multiple Access (CDMA) systems, Time Division Multiple
Access (TDMA) systems, Frequency Division Multiple Access (FDMA)
systems, and Orthogonal Frequency Division Multiple Access (OFDMA)
systems.
[0006] As the demand for high-rate and multimedia data services
rapidly grows, there has been an effort toward implementation of
efficient and robust communication systems with enhanced
performance. For example, in recent years, users have started to
replace fixed line communications with mobile communications and
have increasingly demanded great voice quality, reliable service,
and low prices. In addition to mobile telephone networks currently
in place, a new class of small base stations has emerged, which can
be installed in the home of a user and provide indoor wireless
coverage to mobile units using existing broadband Internet
connections. Such personal miniature base stations are generally
known as access point base stations, or, alternatively, Home Node B
(HNB) or Femto cells. Typically, such miniature base stations are
connected to the Internet and the network of a mobile operator via
a Digital Subscriber Line (DSL) router, cable modem, or the
like.
[0007] Wireless communication systems can be configured to include
a series of wireless access points, which can provide coverage for
respective locations within the system. Such a network structure is
generally referred to as a cellular network structure, and access
points and/or the locations they respectively serve in the network
are generally referred to as cells.
[0008] Further, in a multiple-in-multiple-out (MIMO) communication
system, multiple sources and/or destinations (e.g., corresponding
to respective antennas) can be utilized for the transmission and
reception of data, control signaling, and/or other information
between devices in the communication system. The use of multiple
sources and/or destinations for respective transmissions in
connection with a MIMO communication system has been shown to yield
higher data rates, improved signal quality, and other such benefits
over single-input and/or single-output communication systems in
some cases. One example of a MIMO communication system is a Network
MIMO (N-MIMO) or Coordinated Multipoint (CoMP) system, in which a
plurality of cells can cooperate to exchange information with one
or more receiving devices, such as user equipment units (UEs) or
the like. In such a wireless network implementation, it would be
desirable to implement various improved techniques for selecting
cooperation strategies and/or projected data rates for respective
network users in order to enhance performance gains realized for
the respective users via CoMP communication.
SUMMARY
[0009] The following presents a simplified summary of various
aspects of the claimed subject matter in order to provide a basic
understanding of such aspects. This summary is not an extensive
overview of all contemplated aspects, and is intended to neither
identify key or critical elements nor delineate the scope of such
aspects. Its sole purpose is to present some concepts of the
disclosed aspects in a simplified form as a prelude to the more
detailed description that is presented later.
[0010] According to an aspect, a method is described herein. The
method can comprise identifying a set of network users; obtaining
information relating to signal qualities identified by respective
network users and interference levels observed by the respective
network users; and computing per-user projected rates for network
multiple-in-multiple-out (N-MIMO) communication with the respective
network users based at least in part on obtained information
relating to the signal qualities and interference levels of the
respective network users.
[0011] A second aspect described herein relates to a wireless
communications apparatus, which can comprise a memory that stores
data relating to a set of user equipment units (UEs). The wireless
communications apparatus can further comprise a processor
configured to identify information relating to signal qualities and
interference levels associated with respective UEs and to compute
per-UE projected rates for Coordinated Multipoint (COMP)
communication with the respective UEs based at least in part on
identified information relating to the respective UEs.
[0012] A third aspect relates to an apparatus, which can comprise
means for obtaining channel state information from one or more
terminals; means for estimating carrier and interference levels
associated with the one or more terminals based on the channel
state information; and means for calculating projected rates for
the one or more terminals as a function of estimated carrier and
interference levels associated with the one or more terminals.
[0013] A fourth aspect relates to a computer program product, which
can comprise a computer-readable medium that comprises code for
causing a computer to obtain channel state information from one or
more UEs; code for causing a computer to estimate carrier and
interference levels associated with the one or more UEs based on
the channel state information; and code for causing a computer to
calculate projected rates for the one or more UEs as a function of
estimated carrier and interference levels associated with the one
or more UEs.
[0014] A fifth aspect described herein relates to a method operable
in a wireless communication system. The method can comprise
identifying an amount of processing loss incurred in communication
with at least one associated base station and reporting the amount
of processing loss as feedback to the at least one associated base
station.
[0015] A sixth aspect described herein relates to a wireless
communications apparatus that can comprise a memory that stores
data relating to at least one serving network node. The wireless
communications apparatus can further comprise a processor
configured to determine a processing loss associated with
communication to the at least one serving network node and to
report the processing loss as feedback to the at least one serving
network node.
[0016] A seventh aspect relates to an apparatus operable in a
wireless communication system. The apparatus can comprise means for
identifying feedback information relating to device implementation
loss associated with the apparatus and means for submitting the
feedback information to one or more serving base stations.
[0017] An eighth aspect described herein relates to a computer
program product, which can include a computer-readable medium that
comprises code for causing a computer to identify at least one
serving network node; code for causing a computer to determine a
processing loss associated with communication to the at least one
serving network node; and code for causing a computer to report the
processing loss as feedback to the at least one serving network
node.
[0018] A ninth aspect described herein relates to a method operable
in a wireless communication system. The method can comprise
identifying information relating to an extent of interference
nulling capability of an associated receiver and reporting
identified information relating to the extent of interference
nulling capability of the associated receiver to at least one
serving network node.
[0019] A tenth aspect described herein relates to a wireless
communications apparatus, which can comprise a memory that stores
data relating to at least one serving network node. The wireless
communications apparatus can further comprise a processor
configured to generate an indicator of interference nulling
capability of a receiver associated with the wireless
communications apparatus and to report the indicator as feedback to
the at least one serving network node.
[0020] An eleventh aspect relates to an apparatus, which can
comprise means for identifying feedback information relating to
receiver nulling capability of the apparatus and means for
submitting the feedback information to one or more serving base
stations.
[0021] A twelfth aspect relates to a computer program product,
which can comprise a computer-readable medium that comprises code
for causing a computer to identify at least one serving network
node; code for causing a computer to generate an indicator of
interference nulling capability of a receiver associated with the
apparatus; and code for causing a computer to report the indicator
as feedback to the at least one serving network node.
[0022] To the accomplishment of the foregoing and related ends, one
or more aspects of the claimed subject matter comprise the features
hereinafter fully described and particularly pointed out in the
claims. The following description and the annexed drawings set
forth in detail certain illustrative aspects of the claimed subject
matter. These aspects are indicative, however, of but a few of the
various ways in which the principles of the claimed subject matter
can be employed. Further, the disclosed aspects are intended to
include all such aspects and their equivalents.
BRIEF DESCRIPTION OF THE DRAWINGS
[0023] FIG. 1 is a block diagram of a system for performing
marginal utility and projected rate computation within a
cooperative wireless communication environment in accordance with
various aspects.
[0024] FIG. 2 illustrates an example cooperative communication
deployment that can implement various aspects described herein.
[0025] FIG. 3 is a block diagram of a system for estimating a
per-user projected rate based on user processing loss in accordance
with various aspects.
[0026] FIG. 4 is a block diagram of a system for estimating a
per-user projected rate based on receiver nulling capability of
respective users in accordance with various aspects.
[0027] FIG. 5 is a block diagram of a system for optimizing
per-user marginal utility computations in accordance with various
aspects.
[0028] FIG. 6 is a block diagram of a system for selecting a
cooperation strategy for communication between respective cell
sites and respective terminal devices in a wireless communication
system in accordance with various aspects.
[0029] FIGS. 7-9 are flow diagrams of respective methodologies for
calculating per-user projected rates associated with a cooperative
network transmission scheme.
[0030] FIGS. 10-11 are flow diagrams of respective methodologies
for identifying and communicating feedback relating to a
cooperative network transmission deployment.
[0031] FIGS. 12-13 are block diagrams of respective apparatus that
facilitate initialization and use of respective cooperation
strategies within a wireless communication environment.
[0032] FIG. 14 illustrates an example system that facilitates
cooperative multipoint communication in accordance with various
aspects described herein.
[0033] FIG. 15 illustrates an example wireless communication system
in accordance with various aspects set forth herein.
[0034] FIG. 16 is a block diagram illustrating an example wireless
communication system in which various aspects described herein can
function.
[0035] FIG. 17 illustrates an example communication system that
enables deployment of access point base stations within a network
environment.
DETAILED DESCRIPTION
[0036] Various aspects of the claimed subject matter are now
described with reference to the drawings, wherein like reference
numerals are used to refer to like elements throughout. In the
following description, for purposes of explanation, numerous
specific details are set forth in order to provide a thorough
understanding of one or more aspects. It may be evident, however,
that such aspect(s) may be practiced without these specific
details. In other instances, well-known structures and devices are
shown in block diagram form in order to facilitate describing one
or more aspects.
[0037] As used in this application, the terms "component,"
"module," "system," and the like are intended to refer to a
computer-related entity, either hardware, firmware, a combination
of hardware and software, software, or software in execution. For
example, a component can be, but is not limited to being, a process
running on a processor, an integrated circuit, an object, an
executable, a thread of execution, a program, and/or a computer. By
way of illustration, both an application running on a computing
device and the computing device can be a component. One or more
components can reside within a process and/or thread of execution
and a component can be localized on one computer and/or distributed
between two or more computers. In addition, these components can
execute from various computer readable media having various data
structures stored thereon. The components can communicate by way of
local and/or remote processes such as in accordance with a signal
having one or more data packets (e.g., data from one component
interacting with another component in a local system, distributed
system, and/or across a network such as the Internet with other
systems by way of the signal).
[0038] Furthermore, various aspects are described herein in
connection with a wireless terminal and/or a base station. A
wireless terminal can refer to a device providing voice and/or data
connectivity to a user. A wireless terminal can be connected to a
computing device such as a laptop computer or desktop computer, or
it can be a self contained device such as a personal digital
assistant (PDA). A wireless terminal can also be called a system, a
subscriber unit, a subscriber station, mobile station, mobile,
remote station, access point, remote terminal, access terminal,
user terminal, user agent, user device, or user equipment (UE). A
wireless terminal can be a subscriber station, wireless device,
cellular telephone, PCS telephone, cordless telephone, a Session
Initiation Protocol (SIP) phone, a wireless local loop (WLL)
station, a personal digital assistant (PDA), a handheld device
having wireless connection capability, or other processing device
connected to a wireless modem. A base station (e.g., access point
or Node B) can refer to a device in an access network that
communicates over the air-interface, through one or more sectors,
with wireless terminals. The base station can act as a router
between the wireless terminal and the rest of the access network,
which can include an Internet Protocol (IP) network, by converting
received air-interface frames to IP packets. The base station also
coordinates management of attributes for the air interface.
[0039] Moreover, various functions described herein can be
implemented in hardware, software, firmware, or any combination
thereof. If implemented in software, the functions can be stored on
or transmitted over as one or more instructions or code on a
computer-readable medium. Computer-readable media includes both
computer storage media and communication media including any medium
that facilitates transfer of a computer program from one place to
another. A storage media can be any available media that can be
accessed by a computer. By way of example, and not limitation, such
computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or
other optical disk storage, magnetic disk storage or other magnetic
storage devices, or any other medium that can be used to carry or
store desired program code in the form of instructions or data
structures and that can be accessed by a computer. Also, any
connection is properly termed a computer-readable medium. For
example, if the software is transmitted from a website, server, or
other remote source using a coaxial cable, fiber optic cable,
twisted pair, digital subscriber line (DSL), or wireless
technologies such as infrared, radio, and microwave, then the
coaxial cable, fiber optic cable, twisted pair, DSL, or wireless
technologies such as infrared, radio, and microwave are included in
the definition of medium. Disk and disc, as used herein, includes
compact disc (CD), laser disc, optical disc, digital versatile disc
(DVD), floppy disk and blu-ray disc (BD), where disks usually
reproduce data magnetically and discs reproduce data optically with
lasers. Combinations of the above should also be included within
the scope of computer-readable media.
[0040] Various techniques described herein can be used for various
wireless communication systems, such as Code Division Multiple
Access (CDMA) systems, Time Division Multiple Access (TDMA)
systems, Frequency Division Multiple Access (FDMA) systems,
Orthogonal Frequency Division Multiple Access (OFDMA) systems,
Single Carrier FDMA (SC-FDMA) systems, and other such systems. The
terms "system" and "network" are often used herein interchangeably.
A CDMA system can implement a radio technology such as Universal
Terrestrial Radio Access (UTRA), CDMA2000, etc. UTRA includes
Wideband-CDMA (W-CDMA) and other variants of CDMA. Additionally,
CDMA2000 covers the IS-2000, IS-95 and IS-856 standards. A TDMA
system can implement a radio technology such as Global System for
Mobile Communications (GSM). An OFDMA system can implement a radio
technology such as Evolved UTRA (E-UTRA), Ultra Mobile Broadband
(UMB), IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20,
Flash-OFDM.RTM., etc. UTRA and E-UTRA are part of Universal Mobile
Telecommunication System (UMTS). 3GPP Long Term Evolution (LTE) is
an upcoming release that uses E-UTRA, which employs OFDMA on the
downlink and SC-FDMA on the uplink. UTRA, E-UTRA, UMTS, LTE and GSM
are described in documents from an organization named "3rd
Generation Partnership Project" (3GPP). Further, CDMA2000 and UMB
are described in documents from an organization named "3rd
Generation Partnership Project 2" (3GPP2).
[0041] Various aspects will be presented in terms of systems that
can include a number of devices, components, modules, and the like.
It is to be understood and appreciated that the various systems can
include additional devices, components, modules, etc. and/or can
not include all of the devices, components, modules etc. discussed
in connection with the figures. A combination of these approaches
can also be used.
[0042] Referring now to the drawings, FIG. 1 illustrates a system
100 for performing marginal utility and projected rate computation
within a cooperative wireless communication environment in
accordance with various aspects. As FIG. 1 illustrates, system 100
can include one or more network cells (e.g., Node Bs, Evolved Node
Bs (eNBs), base stations, access points, etc.) 110, which can
communicate with respective user equipment units (UEs, also
referred to as mobile stations, terminals, user devices, etc.) 120.
In one example, respective cells 110 can correspond to and/or
provide communication coverage for any suitable coverage area, such
as an area associated with a macro cell, a femto cell (e.g., an
access point base station or Home Node B (HNB)), and/or any other
suitable type of coverage area.
[0043] In accordance with one aspect, a given UE 120 can
communicate with any suitable number of network cells 110. For
example, a UE 120 can conduct one or more uplink (UL, also referred
to as reverse link (RL)) communications to a cell 110, and
respective cells 110 can conduct one or more downlink (DL, also
referred to as forward link (FL)) communications to the UE 120. In
one example, system 100 can utilize one or more network
multiple-in-multiple-out (Network MIMO or N-MIMO), cooperative
multipoint (COMP), and/or other techniques, by which a single UE
120 is enabled to communicate with a plurality of disparate cells
110 and/or sectors thereof. Additionally or alternatively,
communication between a cell 110 and a UE 120 can result in a
strong dominant interference to other nearby cells 110 and/or UEs
120. For example, if a UE 120 is located at the edge of an area
corresponding to a cell 110 serving the UE 120, communication
between the UE 120 and its serving cell can cause interference to
one or more other cells 110 within range of the UE 120 with which
the UE 120 is not communicating under various circumstances. This
can occur, for example, in a system that includes femto cells if a
UE 120 is located within the coverage area of a femto cell, which
in turn is embedded into the coverage area of a macro cell.
[0044] In accordance with another aspect, respective cells 110 in
system 100 can coordinate pursuant to one or more cooperation
strategies in order to increase data rates associated with
communication with a given UE 120 and/or to reduce interference
caused to other cells 110 and/or UEs 120 in system 100. In one
example, respective cells 110 in system 100 can be operable to
utilize a plurality of cooperation techniques for transmission to
one or more UEs 120, such as coordinated silencing (CS), joint
transmission (JT) via inter-eNodeB (inter-cell) packet sharing,
coordinated beamforming (CBF), and/or any other suitable cell
cooperation technique(s) as generally known in the art. In another
example, various operational aspects of system 100 such as
respective cell cooperation techniques to be utilized for
communication, cells 110 to be utilized for such cooperation
techniques, and respective UEs 120 to be served via cooperative
communication, can be based at least in part on marginal utility
calculations performed by one or more cells 110 (e.g., via a
utility computation module 112) and/or any other suitable
metric.
[0045] In one example, utility associated with a given UE 120 can
be defined in terms of channel quality, user priority level, or the
like. In accordance with one aspect, utility computation module 112
can compute one or more channel quality metrics for a given UE 120
by estimating and/or otherwise assessing a channel component and an
interference component of respective signals observed by the UE
120. Utility computation module 112 can utilize, for example, a
channel predictor 114, an interference predictor 116, and/or any
other suitable component(s) in accordance with various aspects
herein to obtain channel and/or interference estimates for a given
UE 120. In one example, information relating to channel quality
and/or interference levels observed by a UE 120 can be reported
from the UE 120 to a computing cell 110 via a channel/interference
feedback module 122 and/or any other suitable means.
[0046] In accordance with a further aspect, a cell 110 in system
100 can utilize a projected rate computation module 118, which can
be utilized in addition to and/or in lieu of utility computation
module 112 to calculate per-user projected rates for respective
associated UEs 120. In one example, a projected rate associated
with a given UE 120 can correspond to an anticipated channel
quality (e.g., given in terms of a Channel Quality Indicator or
CQI) for the UE 120 based on various forms of cooperative
transmission to the UE 120 (e.g., transmission by the computing
cell alone, cooperative transmission by the computing cell and one
or more other cells, etc.). Additionally or alternatively, a
projected rate as computed by projected rate computation module 118
for a given UE 120 can correspond to an estimated data rate for the
UE 120 based on a combination of conventional data rate projection
techniques and signal/interference component estimates obtained via
channel predictor 114 and/or interference predictor 116. Specific
examples of techniques that can be utilized to compute projected
rates for respective UEs 120 are provided in further detail
herein.
[0047] In one example, projected rate computation module 118 can
leverage a general form for computing projected per-UE rates based
on various factors. These factors can include, for example,
propagation channels for respective links involved in a utilized
cooperation strategy (e.g., taking into account power and bandwidth
resources allocated per link); channel prediction accuracy based on
projected downlink estimation error at respective UEs 120 and
corresponding feedback delay; anticipated interference levels from
cooperative and non-cooperative network nodes (e.g., cells 110
and/or UEs 120), taking into account spatial interference
structures as applicable; and/or any other suitable factors. In one
example, respective UEs 120 in system 100 can provide information
relating to downlink estimation errors, feedback delay, UE
processing loss, interference nulling capability, and/or other
information relating to the operational capabilities of the
respective UEs 120 to respective cells 110 via a UE capability
feedback module 124 and/or any other suitable means. Various
examples of information relating to UE capabilities that can be
reported by UEs 120 in system 100, as well as techniques by which
such information can be processed by respective cells 110 in system
100, are described in further detail herein.
[0048] In accordance with one aspect, respective cells 110 in
system 100 can perform marginal utility and/or projected rate
computations for a given UE 120 based on various requirements for
channel state information at the transmitter (CSIT). CSIT
requirements can vary, for example, based on a cooperation strategy
employed by respective cells 110 with respect to a given UE 120. By
way of specific example, it can be appreciated that CSIT
requirements associated with iterative signal processing and/or CBF
can differ substantially between CSIT requirements for CS. In one
example, a cell 110 can utilize an assumption of accurate CSIT at
moderate to high post-processing carrier to interference (C/I)
levels in order to employ first order approximation of an
associated CSIT effect. Additionally or alternatively, in the event
that a substantially high error effect (e.g., due to spatial error)
is encountered, CS can be favored by cell 110 over more complex
signal processing techniques. In accordance with one aspect, a
threshold at which CS is selected over such techniques can be based
on an empirical measure of channel prediction, as described in
further detail herein.
[0049] In accordance with another aspect, projected rate
calculation as performed by projected rate computation module 118
can proceed based on a channel structure as shown in diagram 200 in
FIG. 2. As diagram 200 illustrates, various cooperative network
nodes (e.g., located within a predetermined geographic area) can be
utilized to conduct N-MIMO transmission to a set of users, while
various non-cooperative nodes (e.g., located outside the
predetermined geographic area) can cause interference to the
cooperative network nodes and/or their served users in some
cases.
[0050] In one example, based on the structure shown in diagram 200,
the following example definitions and derivations can be made by
projected rate computation module 118 to facilitate projected rate
calculation for a given user. The following examples assume
frequency flat fading and single-user precoded MIMO communication
wherein streams are treated as separate UEs; however, it should be
appreciated that the definitions and derivations described herein
could be extended to any suitable network model. For example, an
extension to selective fading could be facilitated by ignoring
error correlation across resources.
[0051] First, a matrix H can be defined as a M.sub.RX.times.M
channel matrix across all transmitter and receiver antennas (e.g.,
corresponding to network nodes and UEs, respectively) within a
strategy S, wherein M.sub.RX and M.sub.TX correspond to the number
of receiver antennas and the number of transmitter antennas,
respectively. In one example, multiple transmitter (or receiver)
antennas per node (or UE) can be allowed. Further, a
M.sub.TX.times.M.sub.UE transmit beamforming matrix W and a
M.sub.RX.times.M.sub.UE receive beamforming matrix Z can be
defined, wherein M.sub.UE represents the number of UEs for which
rates are computed. In addition, I.sub.u can be defined as receiver
interference covariance contributed to a u-th UE by non-cooperative
nodes. In one example, the above definitions can be leveraged to
define a projected rate for a u-th UE at time t as
R u , t ( S ) = I ( 1 .GAMMA. u C u I u ) , ##EQU00001##
wherein I( ) represents an information rate, .GAMMA..sub.u
represents implementation loss for a u-th UE, and C.sub.u and
I.sub.u respectively represent channel and interference components
associated with a UE, which can be defined as
C.sub.u=|Z.sub.uHW.sub.u|.sup.2 and
I u = Z u I u Z u * + u ' .noteq. u Z u HW u ' 2 , ##EQU00002##
wherein Z.sub.u represents the row of Z associated with UE u and
W.sub.u represents the column of W associated with UE u.
[0052] Subsequently, if projected rate computation module 118
operates under an assumption that the channel estimate as provided
above is a minimum mean square error (MMSE) estimate, projected
rate computation module 118 can utilize the MMSE approximation to
account for channel estimation error together with scheduling
delay. This can be done by, for example, including mismatch
introduced by simplifications and/or imperfect tuning, as defined
as follows:
H = H + .DELTA. H ; [ .DELTA. H : , 1 T , , .DELTA. H : , M TX T ]
T = CN ( 0 , [ 1 , 1 0 0 0 0 0 0 M TX , M TX ] ) ; ##EQU00003## E {
H : , l .DELTA. H : , l ' * } = 0 .A-inverted. 1 .ltoreq. l , l '
.ltoreq. M TX . ##EQU00003.2##
Subsequently, projected rate computation module 118 can approximate
a projected rate based on expected information rate conditioned on
CSIT as follows:
R u , t ( S ) = E { R u , t ( S ) | H } ; ##EQU00004## R u , t ( S
) .apprxeq. I ( 1 .GAMMA. u C u I u ) + 1 .GAMMA. u C u I u I ' ( 1
.GAMMA. u C u I u ) l = 1 M TX a l Z u l , l Z u * ; ##EQU00004.2##
C u = Z u H W u 2 ; ##EQU00004.3## I u = Z u I u Z u * + u '
.noteq. u Z u H W u ' 2 . ##EQU00004.4##
In the above derivations and definitions, {umlaut over (H)},
{umlaut over (W)}, and {umlaut over (Z)} are empirical counterparts
of H, W, and Z obtained by replacing H with {umlaut over (H)}, and
.sub.u is an estimate of I.sub.u.
[0053] As further shown in the above derivations, approximate
conditional expected information rate calculation can be conducted
by projected rate computation module 118 by utilizing weights
a.sub.l that are computed based on by-products of the C/I
calculations described above. In addition, .rho..sub.l,l as used
above corresponds to estimation error covariance matrices that
depend on an exact form of the estimate, which can be utilized to
allow for simple closed form approximations in some cases. In one
example, the weights a.sub.l can be computed using the
following:
a l = 1 C u ( W l , u 2 - C u I u W l , u ' .noteq. u 2 - 2 I u u '
.noteq. u Re { W l , u W l , u ' * X u , u ' * X u , u ' } ) ,
##EQU00005##
wherein {umlaut over (X)}={umlaut over (Z)}{umlaut over (H)}{umlaut
over (W)}. Further, in some cases the summation in the above
equation can be neglected at high C/I levels where, e.g., {umlaut
over (X)}.sub.u,u'.noteq.u.fwdarw.0.
[0054] With further reference to system 100 in FIG. 1, projected
rate computation module 118, with the aid of and/or independently
of utility computation module 112, can facilitate calculation of a
per-user projected rate based on various factors. By way of a first
example, projected rate computation module 118 can utilize a
unified projected rate calculation rule, which can be based on a
first order expansion of the average information rate and/or any
other suitable parameters. In accordance with one aspect, a
projected rate computed by projected rate computation module 118
pursuant to a unified projected rate calculation rule can be
configured to be a sufficiently accurate approximation for JT, CBF,
and/or other suitable operations, while additionally being
sufficiently accurate for CS and/or similar operations. In one
example, channel estimation error of silenced nodes associated with
a projected rate computed using a unified calculation rule can be
substantially large; however, it can be appreciated that such error
can be mitigated via low receive power seen from the silenced nodes
at a corresponding UE 120. In another example, a unified
calculation rule as described above can be modified for high
mobility cases (e.g., with or without correlated antennas).
[0055] By way of a second example, projected rate computation
module 118 can perform ambient interference assessment in the
context of projected rate calculation. In one example, ambient
interference associated with a UE 120 can be determined based on a
number of cells 110 serving the UE 120. For example, in the event
that more than one cell 110 serves a UE 120, ambient interference
associated with the UE 120 can be determined by projected rate
computation module 118 under an assumption of full power
transmission from all non-cooperative nodes within range of the UE
120. Alternatively, loading indicators associated with respective
cells 110 (e.g., provided as feedback from a UE 120 within range of
the cells 110 and/or by the cells 110 themselves over a backhaul
link) can be utilized by projected rate computation module 118 such
that interference can be discounted from nodes indicated as
unloaded. In another example, in the event that a single cell 110
serves a given UE 120, the UE 120 can report an ambient
interference estimate back to projected rate computation module 118
via conventional (e.g., traffic) CQI feedback and/or by any other
suitable means.
[0056] By way of a third example, projected rate computation module
118 can leverage various CSIT estimation considerations in
determining a per-user projected rate. For example, projected rate
computation module 118 can track long-term statistics of respective
channels in time, frequency, space, or the like. By doing so, it
can be appreciated that projected rate computation module 118 can
improve channel estimation and extrapolation accuracy for flat
channels in time, frequency, space, or the like. Further, it can be
appreciated that such tracking can enable projected rate
computation module 118 to exploit spatial correlation of co-located
antennas to, for example, facilitate beamforming gains for high
mobility and/or low C/I UEs. In another example, projected rate
computation module 118 can utilize a simple model fitting (e.g., a
one-tap separable infinite impulse response (IIR) model or the
like) to approximate correlations in time, frequency, space, and so
on.
[0057] In accordance with one aspect, projected rate computation
module 118 can further take processing or implementation loss of a
given UE 120 (e.g., a parameter .GAMMA..sub.u corresponding to a
u-th UE as provided in the above derivations) into account in
determining a projected rate for the UE 120. This is illustrated in
further detail by diagram 300 in FIG. 3. In conventional systems
involving a single cell communicating with a single UE, CQI
information is generally reported from the UE to the cell as a
maximum supportable data rate as opposed to interference parameters
for respective non-serving cells. However, it can be appreciated
that such a generalized report does not provide information
regarding processing loss incurred by the UE as a result of, for
example, channel implementations utilized by the UE, soft decoding
techniques leveraged by the UE, or other such causes. Instead, such
processing or implementation loss is absorbed into the generalized
CQI reports provided by the UE. Further, it can be appreciated that
processing loss associated with a given UE does not scale for
N-MIMO communication (e.g., for an increasing number of serving
cells), as strategy selection is generally performed by the
network.
[0058] In the context of N-MIMO or CoMP communication, one or more
cells 110 associated with a given UE 120 can facilitate selection
of respective cells 110 to be involved in a given communication
with the UE 120, and as a result channel information and
interference can be observed at the UE 120 from a plurality of
different cells 110. Subsequently, in a manner similar to that
described above with respect to system 100, carrier and
interference estimates corresponding to various cells 110 and
corresponding UEs 120 can be obtained, which can be leveraged by
projected rate computation module 118 to map respective UEs 120 to
projected data rates. Accordingly, projected rate computation
module 118 can utilize information relating to processing loss of
various UEs 120 to aid in determining per-user data rates
corresponding to respective UEs 120.
[0059] In accordance with one aspect, information relating to user
processing or implementation loss can be made known to projected
rate computation module 118 and/or utility computation module 112
in various manners. As a first example, processing loss can be
defined as a UE-specific parameter, which can be provided as
feedback from respective UEs 120 via an associated processing loss
indicator module 312 and/or other suitable means. Thus, for
example, UE 120 can be configured to provide long-form feedback to
cell 110 that includes one or more bits relating to a processing
loss associated with UE 120 (e.g., in dB and/or any other suitable
unit(s)) via processing loss indicator module 312, such that the
processing loss information can subsequently be utilized by cell
110 in making scheduling decisions. As a second example, a maximum
processing loss can be defined within system 300 for respective UEs
and/or groups of UEs (e.g., per UE category) via a minimum
performance specification (MPS) for system 300 or the like. A
maximum processing loss obtained in this manner can serve as a
limit on processing loss reported by a given UE 120, or
alternatively a maximum processing loss defined for a given UE 120
or UE category to which the UE 120 belongs can be utilized by
projected rate computation module 118 as a default or assumed
processing loss for the UE 120 in performing projected rate
calculation.
[0060] In accordance with an additional aspect, respective UEs 120
in a wireless communication system can be configured to include
receiver interference nulling capability and/or similar capability,
which can be taken into account by projected rate computation
module 118 in determining a projected rate for the respective UEs
120. This is illustrated in further detail by diagram 400 in FIG.
4.
[0061] As illustrated in system 400, a UE 120 can include a
receiver nulling module 412 and/or other similar mechanisms, which
can be utilized by UE 120 to filter and/or otherwise eliminate
interference from one or more network nodes. By way of specific
example, a UE 120 equipped with two or more receive antennas and
corresponding receiver nulling capability via a receiver nulling
module 412 can be located in a network environment that includes a
serving macro cell and a non-serving femto cell (e.g., a restricted
access cell that UE 120 does not have permission to access) that is
sufficiently proximate to UE 120 to cause the femto cell to be a
dominant interferer for UE 120. In such an example, in the event
that no additional dominant interferers are present and channels
associated with the serving macro cell and non-serving femto cell
are substantially static, UE 120 can leverage receiver nulling
module 412 in order to build a filter to null interference caused
by the non-serving femto cell. As a result, it can be appreciated
that receiver interference nulling capability of a UE 120 can
substantially change post-processing C/I levels associated with the
UE 120 due to the fact that the interference nulling in this manner
enables high channel quality to be maintained with minimal
cooperation between cells in a dominant interferer scenario. Thus,
in accordance with one aspect, a projected rate computation module
118, a utility computation module 112, and/or other suitable
components of a network cell 110 can account for receiver nulling
gains in determining per-user projected rates, thereby
substantially improving strategy selection performance.
[0062] In accordance with one aspect, information relating to
receiver nulling capability of a UE 120 can be made known to
respective cells 110 in system 400 in various manners. For example,
UE capabilities can be defined in terms of receiver interference
nulling, which can be provided to a given cell 110 via a receiver
nulling indicator 414 and/or other suitable means of a UE 120,
based on which a projected rate computation module 118 can account
for the specific nulling capabilities of the UE 120 (e.g., in terms
of a maximum amount of interference, number of interferers, etc.,
capable of being nulled) in determining a projected rate for UE
120. Defining and facilitating feedback of receiver nulling
capability in this manner can, in one example, assume spatial
receiver MMSE with a maximum processing loss enforced through
performance tests or the like.
[0063] As an alternative example, minimum nulling requirements can
be defined within system 400 for respective UEs and/or groups of
UEs (e.g., per UE category) via network-wide requirements
associated with respective UEs 120. By way of example, a UE 120
with n receive antennas that is capable of n-th order MIMO can be
mandated to support receiver interference nulling. More
particularly, RX nulling capability for a given UE 120 can be
mandated via an MPS and/or other suitable specification based on UE
category or the like. For instance, a UE 120 which is capable of
supporting n-th order MIMO can be mandated to be capable of nulling
(n-1) dominant interferers. More generally, respective UEs 120 can
be mandated such that a UE 120 can be configured to simultaneously
support m MIMO streams and null up to k dominant interferers, where
(m+k)<n. This can be achieved by, for example, implementing
minimum mean square error (MMSE) receiver techniques at a given UE
120.
[0064] A minimum nulling capability level obtained in this manner
can serve as a floor on nulling capability reported by a given UE
120, or alternatively respective cells 110 can assume that
respective UEs 120 comply with the mandated nulling requirements
and base scheduling decisions on the mandated requirements.
[0065] Referring next to FIG. 5, a block diagram of a system 500
for optimizing per-user marginal utility computations in accordance
with various aspects is illustrated. As shown in FIG. 5, system 500
can include one or more cells 110, which can communicate with
respective associated UEs 120 as generally described herein. In one
example, cell 110 can include a utility computation module 112,
which can facilitate calculation of marginal utility parameters
associated with respective UEs 120 in connection with selection of
a cooperation strategy to be utilized for one or more UEs 120. As
system 500 further illustrates, a cell 110 can further include a
utility optimization module 512, which can be utilized to optimize
utility parameters calculated by utility computation module
112.
[0066] In accordance with one aspect, utility optimization module
512 can perform transmit processing optimization via strategy
utility maximization. This can be achieved using, for example, one
or more iterative utility maximization algorithms (e.g., algorithms
similar to iterative pricing), wherein an iterative search is
performed at respective network nodes (e.g., cells 110, sectors
within cells 110, etc.) for respective candidate cooperation
strategies. In one example, utility optimization module 512 can
take into account various cooperation technique constraints, which
can be, for example, reflected in constraints on the beam
coefficients of various nodes. In another example, utility
optimization module 512 can utilize first order extension to update
respective beam weights at each iteration until convergence. In
various implementations, convergence can be made dependent on an
algorithm starting point.
[0067] The algorithm starting point can, in accordance with another
aspect, be selected in a variety of manners. For example, a
starting point can be selected via zero-forcing (ZF) across
respective cooperating nodes, maximum ratio combining (MRC) and/or
MMSE-based approaches, or the like. In one example, power
allocation techniques can be applied in addition to ZF and/or
MRC.
[0068] In accordance with another aspect, utility optimization
module 512 can utilize iterative processing, which can be conducted
as follows. It should be appreciated that iterative processing as
performed based on the following discussion can utilize a
substantial portion of the assumptions and notations utilized above
with respect to projected rate calculation. Initially, utility of a
marginal strategy can be expressed by utility optimization module
512 as a function of C/I values of respective UEs 120 served by the
strategy (e.g., based on single-user precoded MIMO, wherein streams
are treated as separate UEs 120), or
U t ( S ) = u .di-elect cons. Y ( S ) p u , t R u , t ( S ) , where
R u , t ( S ) = I ( 1 .GAMMA. u C u I u ) ##EQU00006##
as noted above. Based on this expression, utility optimization
module 512 can calculate derivatives of the strategy utility with
respect to the C/I values of the involved UEs 120 as
.differential. U t ( S ) .differential. ( C u / I u ) , u .di-elect
cons. Y ( S ) = p u , t .GAMMA. u I ' ( 1 .GAMMA. u C u I u ) .
##EQU00007##
Accordingly, based on a notation that defines U.sub.t(S(W)) as the
utility associated with strategy S based on transmit beamforming
matrix W, utility optimization module 512 can determine a proper
selection of Z subject to H and W by solving for a variable
.PHI..sub.u in the following:
U t ( S ( W + .DELTA. W ) ) = U t ( S ( W ) ) + u .di-elect cons. Y
( S ) Re { W u * H * .PHI. u .DELTA. W u } + O ( .DELTA. W 2 ) ;
##EQU00008## .PHI. u = 2 I u .differential. U t ( S )
.differential. ( C u / I u ) Z u * Z u - u ' .noteq. u 2 I u
.differential. U t ( S ) .differential. ( C u / I u ) C u ' I u ' Z
u ' * Z u ' . ##EQU00008.2##
[0069] In accordance with a further aspect, upon obtaining a
starting point for optimization for a value of W and a
corresponding value of Z (e.g., based on ZF, MRC, MMSE, etc.),
utility optimization module 512 can iterative conduct the following
optimization procedure. First, utility optimization module 512 can
calculate C/I levels for respective UEs 120 and update .PHI..sub.u
accordingly based on the latest values of W and Z. Next, a
tentative update of W can be defined according to the utility
gradient as W.sub.u:=W.sub.u+.mu.H*.PHI..sub.uHW.sub.u for u
.epsilon. Y(S). Subsequently, utility optimization module 512 can
modify W to reflect respective applicable constraints. For example,
entries W.sub.l,u in W can be zeroed out if transmitter l is not
serving UE u. In addition, W can be scaled to ensure that maximum
power constraints of respective transmitters are not exceeded. Upon
modifying W, Z can be updated based on the modifications to W.
Finally, if the corresponding increase in U.sub.t(S(W)) is less
than a predefined threshold, or a maximum number of iterations is
reached, optimization can complete; otherwise, the above steps can
be repeated.
[0070] In accordance with an additional aspect, utility
optimization module 512 can obtain a starting point for the above
procedure based on zero-forcing with water filling. More
particularly, utility optimization module 512 can start with a
normalized zero-forcing scheme W having the same transmitter energy
for substantially all UEs 120. Based on this scheme, water filling
can be defined as follows:
W _ = H * ( HH * ) - 1 diag { ( HH * ) - 1 } - 1 / 2 ; ##EQU00009##
W = W _ diag { P u } u .di-elect cons. Y ( S ) . ##EQU00009.2##
Next, utility optimization module 512 can select the total powers
P.sub.u allocated per UE according to water filling in a way that
maximizes U.sub.t(S(W)). For example, it can be appreciated that
generalized water filling over {P.sub.u} can apply to the
sum-utility
U t ( S ) = u .di-elect cons. Y ( S ) p u , t I ( P u .GAMMA. u Z u
HW u 2 Z u I u Z u * ) . ##EQU00010##
Based on this formulation, I ( . . . ) can be approximated by the
unconstrained capacity, and a constraint on the total transmit
power can be given by
u = Y ( S ) P u . ##EQU00011##
Subsequently, utility optimization module 512 can normalize an
obtained solution to meet per-transmit antenna power constraints.
While the above example is specific to ZF, it should be appreciated
that similar techniques could be utilized for MRC, MMSE, and/or any
other suitable technique(s).
[0071] Turning to FIG. 6, a block diagram of a system 600 for
selecting a cooperation strategy for communication between
respective cell sites (e.g., cells 110) and respective terminal
devices (e.g., UEs 120) in a wireless communication system is
illustrated. As shown in system 600, respective cells 110 can
include a utility computation module 112 for determining marginal
utility associated with respective users as generally described
above, based on which a cooperation strategy selector 620 can
coordinate respective transmissions between cells 110 and UEs 120
in system 600. In general, cooperation strategy selector 620 can be
utilized by a cell 110 to compute and/or make scheduling decisions
relating to node clustering, scheduling, forms of cooperative
transmission to be utilized, and so on. To these ends, cooperation
strategy selector 620 can include a node selector 622 for
scheduling respective nodes to be utilized for communication with a
given UE 120, a cooperation type selector 624 to determine a form
of cooperation to utilize for communication with a given UE 120,
and/or other suitable mechanisms.
[0072] In accordance with one aspect, a cooperation strategy can be
selected by cooperation type selector 624 based on factors such as
UE mobility (e.g., as determined by a mobility analyzer 612), C/I
levels associated with respective UEs 120 (e.g., as identified by a
channel/interference analyzer 614), capabilities of backhaul links
between respective cells, or the like. By way of example,
cooperation type selector 624 can select CS and/or another similar
simple form of cell cooperation in the case of high-mobility UEs
and/or rapidly changing channel conditions associated with a given
UE 120. Additionally or alternatively, if mobility of a given UE
120 is determined to be low, or a high degree of antenna
correlation is present with respect to the UE 120, more advanced
cooperation techniques such as JT via inter-cell packet sharing
(e.g., in the case of a relatively slow backhaul link between cells
110) or CBF (e.g., in the case of a relatively fast backhaul link
between cells 110) can be selected.
[0073] In accordance with another aspect, a projected rate
associated with respective UEs (e.g., as computed in accordance
with various examples described above) can be utilized along with
factors such as backhaul bandwidth, latency constraints, or the
like, to select between respective cooperation techniques. For
example, cooperation type selector 624 can rule out a JT technique
using backhaul bandwidth and latency uncertainty based on
associated a priori and/or long-term backhaul link classifications.
In another example, CSIT delivery delay and accuracy, as well as
scheduling delay and/or other suitable factors, can be factored in
projected rate calculation.
[0074] By way of specific example, cooperation type selector 624
can utilize a set of cooperation technique selection rules as
follows. First, cooperation type selector 624 can rule out a JT
technique based on a long-term backhaul link classification.
Further, cooperation type selector 624 can consider CBF techniques
over JT in the event that a ratio of a combined energy C/I to the
best node C/I is below a predefined threshold. In addition, if an
associated channel prediction error is above a threshold value,
cooperation type selector 624 can consider CS (e.g., in the event
that CBF and/or JT are possible).
[0075] Referring now to FIGS. 7-11, methodologies that can be
performed in accordance with various aspects set forth herein are
illustrated. While, for purposes of simplicity of explanation, the
methodologies are shown and described as a series of acts, it is to
be understood and appreciated that the methodologies are not
limited by the order of acts, as some acts can, in accordance with
one or more aspects, occur in different orders and/or concurrently
with other acts from that shown and described herein. For example,
those skilled in the art will understand and appreciate that a
methodology could alternatively be represented as a series of
interrelated states or events, such as in a state diagram.
Moreover, not all illustrated acts may be required to implement a
methodology in accordance with one or more aspects.
[0076] With reference to FIG. 7, illustrated is a methodology 700
for calculating per-user projected rates associated with a
cooperative network transmission scheme. It is to be appreciated
that methodology 700 can be performed by, for example, a network
cell (e.g., cell 110 in system 100) and/or any other appropriate
network device. Methodology 700 begins at block 702, wherein a set
of users (e.g., UEs 120) are identified. Next, at block 704,
information relating to signal quality identified by respective
users identified at block 702 and interference levels observed by
the respective users is obtained (e.g., by a channel predictor 114
and an interference predictor 116, respectively). Methodology 700
can then conclude at block 706, wherein per-user projected rates
for the respective users identified at block 702 are computed
(e.g., by a projected rate computation module 118) based at least
in part on the information obtained at block 704.
[0077] Turning next to FIG. 8, a flow diagram of a methodology 800
for calculating per-user projected rates based on user processing
loss information is illustrated. Methodology 800 can be performed
by, for example, a base station and/or any other appropriate
network entity. Methodology 800 begins at block 802, wherein an
associated wireless terminal is identified. Methodology 800 can
then proceed to block 804 and/or block 806 from block 802. More
particularly, at block 804, an amount of processing loss associated
with the wireless terminal identified at block 802 is identified
based at least in part on feedback received from the wireless
terminal (e.g., via a processing loss indicator module 312).
Additionally or alternatively, at block 806, an amount of
processing loss associated with the wireless terminal identified at
block 802 is identified based at least in part on a processing loss
limit associated with the wireless terminal or a user category to
which the wireless terminal belongs (e.g., a per-UE or per-UE
category maximum processing loss mandated in an associated MPS
and/or by any other suitable means).
[0078] In accordance with one aspect, methodology 800 can perform
the acts described at block 804, the acts described at block 806,
or a combination thereof. For example, a mandated processing loss
limit associated with a given wireless terminal identified at block
806 can serve as a cap or a floor on a processing loss obtained
from the wireless terminal at block 804. Additionally or
alternatively, a mandated processing loss limit as given at block
806 can be utilized as a default processing loss in the event that
no feedback relating to processing loss is received from the
wireless terminal. In one example, upon completing the acts
described at block 804 and/or block 806, methodology 800 can
conclude at block 808, wherein a projected rate for the wireless
terminal is computed as a function of the amount of processing loss
associated with the wireless terminal as identified at block 804
and/or block 806.
[0079] FIG. 9 illustrates a methodology 900 for calculating
per-user projected rates based on receiver interference nulling
indicators. Methodology 900 can be performed by, for example, a
wireless network node and/or any other suitable network device.
Methodology 900 begins at block 902, wherein an associated UE is
identified. From block 902, methodology can proceed to block 904,
wherein an extent of interference nulling capability of the UE
identified at block 902 is identified based at least in part on
feedback received from the UE (e.g., via a receiver nulling
indicator module 414), and/or to block 906, wherein an extent of
interference nulling capability of the UE is identified based at
least in part on a predefined minimum requirement associated with
the UE or a UE category corresponding to the UE (e.g., as mandated
in an associated network specification and/or otherwise set
throughout an associated communication network).
[0080] In accordance with one aspect, methodology 900 can perform
the acts described at block 904, the acts described at block 906,
or a combination thereof. For example, a mandated minimum nulling
capability associated with a given UE as identified at block 906
can serve as a cap or a floor on interference nulling capability
feedback received at block 904. Additionally or alternatively,
receiver nulling requirements identified at block 906 can be
utilized as a default parameter for the UE identified at block 902
in the event that no feedback relating to interference nulling is
received from the UE. In one example, upon completing the acts
described at block 904 and/or block 906, methodology 900 can
conclude at block 908, wherein a projected rate for the UE
identified at block 902 is computed as a function of the extent of
interference nulling capability indicated by and/or otherwise
associated with the UE at block 904 and/or block 906.
[0081] Referring next to FIG. 10, illustrated is a methodology 1000
for identifying and communicating feedback relating to a
cooperative network transmission deployment. It is to be
appreciated that methodology 1000 can be performed by, for example,
a wireless terminal (e.g., UE 120) and/or any other appropriate
network device. Methodology 1000 begins at block 1002, wherein an
amount of processing loss incurred in communication with at least
one base station (e.g., a cell 110) is identified. In one example,
an amount of processing loss identified at block 1002 can be based
at least in part on a mandated processing loss limit associated
with an entity performing methodology 1000. Thus, for example,
either an actual processing loss or a mandated processing loss can
be identified at block 1002 under various circumstances. Upon
completing the acts described at block 1002, methodology 1000 can
conclude at block 1004, wherein the amount of processing loss
identified at block 1002 is reported as feedback to the at least
one base station (e.g., using a processing loss indicator module
312).
[0082] Turning to FIG. 11, a flow diagram of another methodology
1100 for identifying and communicating feedback relating to a
cooperative network transmission deployment is illustrated.
Methodology 1100 can be performed by, for example, a UE and/or any
other suitable network device. Methodology 1100 begins at block
1102, wherein information relating to an extent of interference
nulling capability of an associated receiver is identified. In one
example, receiver nulling capability as identified at block 1102
can be based at least in part on a system-wide interference nulling
specification associated with an entity performing methodology
1100. Thus, for example, information relating to either actual
interference nulling capability or specified and/or mandated
interference nulling capability can be identified at block 1102
under various circumstances. Upon completing the acts described at
block 1102, methodology 1100 can conclude at block 1104, wherein
the information identified at block 1102 is reported to at least
one serving network node (e.g., using a receiver nulling indicator
module 414).
[0083] Referring next to FIGS. 12-13, respective apparatuses
1200-1300 that can be utilized in accordance with various aspects
described herein are illustrated. It is to be appreciated that
apparatuses 1200-1300 are represented as including functional
blocks, which can be functional blocks that represent functions
implemented by a processor, software, or combination thereof (e.g.,
firmware).
[0084] With reference to FIG. 12, an apparatus 1200 that
facilitates initialization and use of respective cooperation
strategies within a wireless communication environment is
illustrated. Apparatus 1200 can be implemented by a network cell
(e.g., cell 110) and/or another suitable network entity and can
include a module 1202 for obtaining channel state information from
one or more terminals; a module 1204 for estimating carrier and
interference levels associated with the one or more terminals based
on the channel state information; and a module 1206 for calculating
projected rates for the one or more terminals as a function of the
carrier and interference levels associated with the one or more
terminals.
[0085] FIG. 13 illustrates another apparatus 1300 that facilitates
initialization and use of respective cooperation strategies within
a wireless communication environment. Apparatus 1300 can be
implemented by a UE (e.g., UE 120) and/or another suitable network
device and can include a module 1302 for identifying feedback
information relating to device implementation loss and/or receiver
nulling capability and a module 1304 for submitting the feedback
information to be provided to one or more serving base
stations.
[0086] Referring next to FIG. 14, an example system 1400 that
facilitates cooperative multipoint communication in accordance with
various aspects described herein is illustrated. As FIG. 14
illustrates, system 1400 can include respective user devices 1430
that can communicate with one or more associated network cells,
such as serving cell(s) 1410 and auxiliary cell(s) 1420. While the
names "serving cell" and "auxiliary cell" are used to refer to
network cells 1410-1420, it should be appreciated that no
functionality of cells 1410-1420 is intended to be implied by such
naming. For example, an auxiliary cell 1420 can serve a user device
1430 by providing communication coverage for user device 1430 in
addition to, or in place of, a serving cell 1410 in some cases.
Further, cells 1410-1420 can be any of any suitable cell type(s),
including, for example, macro cells, femto cells or Home Node Bs
(HNBs), pico cells, relays, or the like.
[0087] In accordance with one aspect, respective serving cells 1410
and auxiliary cells 1420 can cooperate to perform N-MIMO or CoMP
communication with one or more user devices 1430, thereby improving
the overall throughput and performance of system 1400 as compared
to a conventional wireless communication system in which a user
device connects to a single cell (e.g., a closest and/or strongest
cell). In one example, CoMP and/or other techniques can be utilized
to facilitate cooperation between respective cells 1410-1420,
between respective sectors associated with one or more cells
1410-1420, and/or any other suitable network entities. Such
cooperation can be facilitated by, for example, a TX/RX
coordination module 1412 associated with respective cells 1410-1420
and/or any other suitable mechanism(s). Further, TX/RX coordination
module 1412 can facilitate cooperation between respective network
entities according to any suitable network cooperation
strategy(ies), such as fractional frequency reuse, silencing,
coordinated beamforming, joint transmission, or the like.
[0088] In one example, coordinated beamforming can be conducted
between network nodes associated with respective cells 1410-1420 by
coordinating transmissions from the respective cells 1410-1420 such
that if a transmission to a user device 1430 occurs from a given
cell 1410 or 1420, a beam is chosen to serve the user device 1430
by the given cell 1410 or 1420 such that the transmission to the
user device 1430 is orthogonal or otherwise substantially
mismatched to user devices scheduled on neighboring cells 1410
and/or 1420. By doing so, it can be appreciated that beamforming
gains can be realized for a desired user device 1430 while
simultaneously reducing the effects of interference on neighboring
network devices. In one example, coordinated beamforming can be
facilitated by performing scheduling, beam selection, user
selection (e.g., by selecting user devices 1430 having desirable
beams that substantially limit interference at neighboring
devices), or the like.
[0089] Additionally or alternatively, joint transmission can be
conducted between a plurality of network nodes and a given user
device 1430 by, for example, pooling resources designated for
transmission to a given user device 1430 and transmitting the
pooled resources via multiple distinct network nodes (e.g., nodes
corresponding to a serving cell 1410 as well as an auxiliary cell
1420). In one example, resource pooling among network nodes
corresponding to different cells 1410-1420 can be conducted via a
backhaul link between the cells 1410-1420 and/or any other suitable
mechanism. In another example, similar techniques can be utilized
for uplink joint transmission, wherein a user device 1430 can be
configured to transmit data, control signaling, and/or other
appropriate information to multiple network nodes. For example,
instead of a first cell transmitting a modulation symbol x to a
first user and a second cell transmitting a modulation symbol y to
a second user, the cells can cooperate such that the first cell
transmits ax+by to one or both of the users and the second cell
transmits cx+dy to the same user(s), where a, b, c, and d are
coefficients chosen to optimize the signal-to-noise ratio (SNR) of
the users, system capacity, and/or any other suitable
metric(s).
[0090] In accordance with one aspect, various aspects of uplink and
downlink CoMP communication can be based on feedback provided by
respective user devices 1430. For example, a N-MIMO feedback module
1432 at respective user devices 1430 can be utilized to provide
feedback to various cells 1410-1420, which in turn can utilize a
user feedback processing module 1414 and/or other suitable means to
utilize the feedback in conducting cooperative communication within
system 1400. By way of example, in the case of downlink CoMP
communication, a N-MIMO feedback module 1432 at user device(s) 1430
can facilitate channel reporting to respective cells 1410-1420 of
respective serving cells as well as one or more neighboring
non-cooperative cells. By way of another example, in the case of
uplink CoMP communication, N-MIMO feedback module 1432 can provide
feedback information to respective cells 1410-1420 in combination
with respectively scheduled uplink transmissions to the cells
1410-1420 that can be utilized by the cells 1410-1420 to facilitate
the removal of interference from the corresponding uplink
transmissions.
[0091] Turning to FIG. 15, an exemplary wireless communication
system 1500 is illustrated. In one example, system 1500 can be
configured to support a number of users, in which various disclosed
embodiments and aspects can be implemented. As shown in FIG. 15, by
way of example, system 1500 can provide communication for multiple
cells 1502, (e.g., macro cells 1502a-1502g), with respective cells
being serviced by corresponding access points (AP) 1504 (e.g., APs
1504a-1504g). In one example, one or more cells can be further
divided into respective sectors (not shown).
[0092] As FIG. 15 further illustrates, various access terminals
(ATs) 1506, including ATs 1506a-1506k, can be dispersed throughout
system 1500. In one example, an AT 1506 can communicate with one or
more APs 1504 on a forward link (FL) and/or a reverse link (RL) at
a given moment, depending upon whether the AT is active and whether
it is in soft handoff and/or another similar state. As used herein
and generally in the art, an AT 1506 can also be referred to as a
user equipment (UE), a mobile terminal, and/or any other suitable
nomenclature. In accordance with one aspect, system 1500 can
provide service over a substantially large geographic region. For
example, macro cells 1502a-1502g can provide coverage for a
plurality of blocks in a neighborhood and/or another similarly
suitable coverage area.
[0093] Referring now to FIG. 16, a block diagram illustrating an
example wireless communication system 1600 in which various aspects
described herein can function is provided. In one example, system
1600 is a multiple-input multiple-output (MIMO) system that
includes a transmitter system 1610 and a receiver system 1650. It
should be appreciated, however, that transmitter system 1610 and/or
receiver system 1650 could also be applied to a multi-input
single-output system wherein, for example, multiple transmit
antennas (e.g., on a base station), can transmit one or more symbol
streams to a single antenna device (e.g., a mobile station).
Additionally, it should be appreciated that aspects of transmitter
system 1610 and/or receiver system 1650 described herein could be
utilized in connection with a single output to single input antenna
system.
[0094] In accordance with one aspect, traffic data for a number of
data streams are provided at transmitter system 1610 from a data
source 1612 to a transmit (TX) data processor 1614. In one example,
each data stream can then be transmitted via a respective transmit
antenna 1624. Additionally, TX data processor 1614 can format,
encode, and interleave traffic data for each data stream based on a
particular coding scheme selected for each respective data stream
in order to provide coded data. In one example, the coded data for
each data stream can then be multiplexed with pilot data using OFDM
techniques. The pilot data can be, for example, a known data
pattern that is processed in a known manner. Further, the pilot
data can be used at receiver system 1650 to estimate channel
response. Back at transmitter system 1610, the multiplexed pilot
and coded data for each data stream can be modulated (i.e., symbol
mapped) based on a particular modulation scheme (e.g., BPSK, QSPK,
M-PSK, or M-QAM) selected for each respective data stream in order
to provide modulation symbols. In one example, data rate, coding,
and modulation for each data stream can be determined by
instructions performed on and/or provided by processor 1630.
[0095] Next, modulation symbols for all data streams can be
provided to a TX processor 1620, which can further process the
modulation symbols (e.g., for OFDM). TX MIMO processor 1620 can
then provides N.sub.T modulation symbol streams to N.sub.T
transceivers 1622a through 1622t. In one example, each transceiver
1622 can receive and process a respective symbol stream to provide
one or more analog signals. Each transceiver 1622 can then further
condition (e.g., amplify, filter, and upconvert) the analog signals
to provide a modulated signal suitable for transmission over a MIMO
channel. Accordingly, N.sub.T modulated signals from transceivers
1622a through 1622t can then be transmitted from N.sub.T antennas
1624a through 1624t, respectively.
[0096] In accordance with another aspect, the transmitted modulated
signals can be received at receiver system 1650 by N.sub.R antennas
1652a through 1652r. The received signal from each antenna 1652 can
then be provided to respective transceivers 1654. In one example,
each transceiver 1654 can condition (e.g., filter, amplify, and
downconvert) a respective received signal, digitize the conditioned
signal to provide samples, and then processes the samples to
provide a corresponding "received" symbol stream. An RX MIMO/data
processor 1660 can then receive and process the N.sub.R received
symbol streams from N.sub.R transceivers 1654 based on a particular
receiver processing technique to provide N.sub.T "detected" symbol
streams. In one example, each detected symbol stream can include
symbols that are estimates of the modulation symbols transmitted
for the corresponding data stream. RX processor 1660 can then
process each symbol stream at least in part by demodulating,
deinterleaving, and decoding each detected symbol stream to recover
traffic data for a corresponding data stream. Thus, the processing
by RX processor 1660 can be complementary to that performed by TX
MIMO processor 1620 and TX data processor 1616 at transmitter
system 1610. RX processor 1660 can additionally provide processed
symbol streams to a data sink 1664.
[0097] In accordance with one aspect, the channel response estimate
generated by RX processor 1660 can be used to perform space/time
processing at the receiver, adjust power levels, change modulation
rates or schemes, and/or other appropriate actions. Additionally,
RX processor 1660 can further estimate channel characteristics such
as, for example, signal-to-noise-and-interference ratios (SNRs) of
the detected symbol streams. RX processor 1660 can then provide
estimated channel characteristics to a processor 1670. In one
example, RX processor 1660 and/or processor 1670 can further derive
an estimate of the "operating" SNR for the system. Processor 1670
can then provide channel state information (CSI), which can
comprise information regarding the communication link and/or the
received data stream. This information can include, for example,
the operating SNR. The CSI can then be processed by a TX data
processor 1618, modulated by a modulator 1680, conditioned by
transceivers 1654a through 1654r, and transmitted back to
transmitter system 1610. In addition, a data source 1616 at
receiver system 1650 can provide additional data to be processed by
TX data processor 1618.
[0098] Back at transmitter system 1610, the modulated signals from
receiver system 1650 can then be received by antennas 1624,
conditioned by transceivers 1622, demodulated by a demodulator
1640, and processed by a RX data processor 1642 to recover the CSI
reported by receiver system 1650. In one example, the reported CSI
can then be provided to processor 1630 and used to determine data
rates as well as coding and modulation schemes to be used for one
or more data streams. The determined coding and modulation schemes
can then be provided to transceivers 1622 for quantization and/or
use in later transmissions to receiver system 1650. Additionally
and/or alternatively, the reported CSI can be used by processor
1630 to generate various controls for TX data processor 1614 and TX
MIMO processor 1620. In another example, CSI and/or other
information processed by RX data processor 1642 can be provided to
a data sink 1644.
[0099] In one example, processor 1630 at transmitter system 1610
and processor 1670 at receiver system 1650 direct operation at
their respective systems. Additionally, memory 1632 at transmitter
system 1610 and memory 1672 at receiver system 1650 can provide
storage for program codes and data used by processors 1630 and
1670, respectively. Further, at receiver system 1650, various
processing techniques can be used to process the N.sub.R received
signals to detect the N.sub.T transmitted symbol streams. These
receiver processing techniques can include spatial and space-time
receiver processing techniques, which can also be referred to as
equalization techniques, and/or "successive nulling/equalization
and interference cancellation" receiver processing techniques,
which can also be referred to as "successive interference
cancellation" or "successive cancellation" receiver processing
techniques.
[0100] FIG. 17 illustrates an example communication system 1700
that enables deployment of access point base stations within a
network environment. As shown in FIG. 17, system 1700 can include
multiple access point base stations (e.g., femto cells or Home Node
B units (HNBs)) such as, for example, HNBs 1710. In one example,
respective HNBs 1710 can be installed in a corresponding small
scale network environment, such as, for example, one or more user
residences 1730. Further, respective HNBs 1710 can be configured to
serve associated and/or alien UE(s) 1720. In accordance with one
aspect, respective HNBs 1710 can be coupled to the Internet 1740
and a mobile operator core network 1750 via a DSL router, a cable
modem, and/or another suitable device (not shown). In accordance
with one aspect, an owner of a femto cell or HNB 1710 can subscribe
to mobile service, such as, for example, 3G/4G mobile service,
offered through mobile operator core network 1750. Accordingly, UE
1720 can be enabled to operate both in a macro cellular environment
1760 and in a residential small scale network environment.
[0101] In one example, UE 1720 can be served by a set of Femto
cells or HNBs 1710 (e.g., HNBs 1710 that reside within a
corresponding user residence 1730) in addition to a macro cell
mobile network 1760. As used herein and generally in the art, a
home femto cell is a base station on which an AT or UE is
authorized to operate on, a guest femto cell refers to a base
station on which an AT or UE is temporarily authorized to operate
on, and an alien femto cell is a base station on which the AT or UE
is not authorized to operate on. In accordance with one aspect, a
femto cell or HNB 1710 can be deployed on a single frequency or on
multiple frequencies, which may overlap with respective macro cell
frequencies.
[0102] It is to be understood that the aspects described herein can
be implemented by hardware, software, firmware, middleware,
microcode, or any combination thereof. When the systems and/or
methods are implemented in software, firmware, middleware or
microcode, program code or code segments, they can be stored in a
machine-readable medium, such as a storage component. A code
segment can represent a procedure, a function, a subprogram, a
program, a routine, a subroutine, a module, a software package, a
class, or any combination of instructions, data structures, or
program statements. A code segment can be coupled to another code
segment or a hardware circuit by passing and/or receiving
information, data, arguments, parameters, or memory contents.
Information, arguments, parameters, data, etc. can be passed,
forwarded, or transmitted using any suitable means including memory
sharing, message passing, token passing, network transmission,
etc.
[0103] For a software implementation, the techniques described
herein can be implemented with modules (e.g., procedures,
functions, and so on) that perform the functions described herein.
The software codes can be stored in memory units and executed by
processors. The memory unit can be implemented within the processor
or external to the processor, in which case it can be
communicatively coupled to the processor via various means as is
known in the art.
[0104] What has been described above includes examples of one or
more aspects. It is, of course, not possible to describe every
conceivable combination of components or methodologies for purposes
of describing the aforementioned aspects, but one of ordinary skill
in the art can recognize that many further combinations and
permutations of various aspects are possible. Accordingly, the
described aspects are intended to embrace all such alterations,
modifications and variations that fall within the spirit and scope
of the appended claims. Furthermore, to the extent that the term
"includes" is used in either the detailed description or the
claims, such term is intended to be inclusive in a manner similar
to the term "comprising" as "comprising" is interpreted when
employed as a transitional word in a claim. Furthermore, the term
"or" as used in either the detailed description or the claims is
meant to be a "non-exclusive or."
* * * * *