U.S. patent application number 14/842592 was filed with the patent office on 2017-03-02 for using compressed beamforming information for optimizing multiple-input multiple-output operations.
The applicant listed for this patent is QUALCOMM Incorporated. Invention is credited to Eugene Baik, Ahmed Ragab Elsherif, Qinghai Gao, Srinivas Katar, Gregory Steele, Ehab Tahir, Didier Johannes Richard van Nee.
Application Number | 20170063438 14/842592 |
Document ID | / |
Family ID | 58096906 |
Filed Date | 2017-03-02 |
United States Patent
Application |
20170063438 |
Kind Code |
A1 |
Baik; Eugene ; et
al. |
March 2, 2017 |
USING COMPRESSED BEAMFORMING INFORMATION FOR OPTIMIZING
MULTIPLE-INPUT MULTIPLE-OUTPUT OPERATIONS
Abstract
Methods, systems, and devices are described for wireless
communication. In one aspect, a method of wireless communication
includes receiving, by a first wireless device, compressed
beamforming information from each of a plurality of stations, the
compressed beamforming information including a feedback
signal-to-noise ratio (SNR) value and compressed feedback matrix.
The method also includes determining a multi-user
signal-to-interference-plus noise ratio (SINR) metric for each of
the plurality of stations based at least in part on the received
feedback SNR values and the received compressed feedback
matrices.
Inventors: |
Baik; Eugene; (San Diego,
CA) ; Elsherif; Ahmed Ragab; (Santa Clara, CA)
; Gao; Qinghai; (Sunnyvale, CA) ; Steele;
Gregory; (Pleasanton, CA) ; Katar; Srinivas;
(Fremont, CA) ; van Nee; Didier Johannes Richard;
(Tull ent Waal, NL) ; Tahir; Ehab; (Mississauga,
CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
QUALCOMM Incorporated |
San Diego |
CA |
US |
|
|
Family ID: |
58096906 |
Appl. No.: |
14/842592 |
Filed: |
September 1, 2015 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04L 5/0023 20130101;
H04L 5/0037 20130101; H04L 5/006 20130101; H04B 7/0617 20130101;
H04B 7/0632 20130101; H04B 7/0452 20130101 |
International
Class: |
H04B 7/04 20060101
H04B007/04; H04W 16/28 20060101 H04W016/28; H04L 5/00 20060101
H04L005/00 |
Claims
1. A method for wireless communication, comprising: receiving, by a
first wireless device, compressed beamforming information from each
of a plurality of stations, the compressed beamforming information
including a feedback signal-to-noise ratio (SNR) value and
compressed feedback matrix; determining, by the first wireless
device, a multi-user signal-to-interference-plus noise ratio (SINR)
metric for each of the plurality of stations based at least in part
on the received feedback SNR values and the received compressed
feedback matrices; and setting, by the first wireless device, a
transmission rate for each of the plurality of stations based at
least in part on the determined multi-user SINR metrics.
2. The method of claim 1, further comprising: forming a multi-user
transmission group from the plurality of stations based at least in
part on the determined multi-user SINR metrics.
3. The method of claim 1, wherein determining the multi-user SINR
metric for each of the plurality of stations further comprises:
determining a beamforming steering matrix based at least in part on
the received SNR values and received compressed feedback matrices;
and determining the multi-user SINR metric for each of the
plurality of stations based at least in part on the determined
beamforming steering matrix.
4. The method of claim 3, further comprising: performing a
subsequent channel sounding procedure prior to performing a
multi-user transmission to a multi-user transmission group formed
based at least in part on an initial channel sounding procedure,
the subsequent channel sounding procedure using the determined
beamforming steering matrix.
5. The method of claim 1, wherein determining the multi-user SINR
metric for a first station of the plurality of stations comprises
using beamforming weights associated with a spatial stream to a
second station of the plurality of stations.
6. The method of claim 1, further comprising: decompressing the
compressed feedback matrices based at least in part on angles
associated with the compressed feedback matrix for each of the
plurality of stations.
7. (canceled)
8. A communications device, comprising: a transceiver to receive
compressed beamforming information from each of a plurality of
stations, the compressed beamforming information including a
feedback signal-to-noise ratio (SNR) value and compressed feedback
matrix; a multi-user signal-to-interference-plus-noise ratio (SINR)
estimator to determine a multi-user SINR metric for each of the
plurality of stations based at least in part on the received
feedback SNR values and the received compressed feedback matrices;
and a modulation and coding scheme (MCS) manager to set a
transmission rate for each of the plurality of stations based at
least in part on the determined multi-user SINR metrics.
9. The communications device of claim 8, further comprising: a
multi-user grouping manager to form a multi-user transmission group
from the plurality of stations based at least in part on the
determined multi-user SINR metrics.
10. The communications device of claim 8, wherein the multi-user
SINR estimator to determine the multi-user SINR metric for each of
the plurality of stations comprises the multi-user SINR estimator
to: determine a beamforming steering matrix based at least in part
on the received SNR values and received compressed feedback
matrices; and determine the multi-user SINR metric for each of the
plurality of stations based at least in part on the determined
beamforming steering matrix.
11. The communications device of claim 10, further comprising: a
multi-user grouping manager to perform a subsequent channel
sounding procedure prior to performing a multi-user transmission to
a multi-user transmission group formed based at least in part on an
initial channel sounding procedure, the subsequent channel sounding
procedure using the determined beamforming steering matrix.
12. The communications device of claim 8, wherein the multi-user
SINR estimator uses beamforming weights associated with a spatial
stream to a second station of the plurality of stations to
determine the multi-user SINR metrics.
13. The communications device of claim 8, further comprising: a
decompressor to decompress the compressed feedback matrices based
at least in part on angles associated with the compressed feedback
matrix for each of the plurality of stations.
14. (canceled)
15. A communications device, comprising: means for receiving
compressed beamforming information from each of a plurality of
stations, the compressed beamforming information including a
feedback signal-to-noise ratio (SNR) value and compressed feedback
matrix; means for determining a multi-user
signal-to-interference-plus noise ratio (SINR) metric for each of
the plurality of stations based at least in part on the received
feedback SNR values and the received compressed feedback matrices;
and means for setting a transmission rate for each of the plurality
of stations based at least in part on the determined multi-user
SINR metrics.
16. The communications device of claim 15, further comprising:
means for forming a multi-user transmission group from the
plurality of stations based at least in part on the determined
multi-user SINR metrics.
17. The communications device of claim 15, wherein the means for
determining the multi-user SINR metric for each of the plurality of
stations is configured to: determine a beamforming steering matrix
based at least in part on the received SNR values and received
compressed feedback matrices; and determine the multi-user SINR
metric for each of the plurality of stations based at least in part
on the determined beamforming steering matrix.
18. The communications device of claim 15, further comprising:
means for performing a subsequent channel sounding procedure prior
to performing a multi-user transmission to a multi-user
transmission group formed based at least in part on an initial
channel sounding procedure, the subsequent channel sounding
procedure using the determined beamforming steering matrix.
19. The communications device of claim 15, wherein the means for
determining the multi-user SINR metric for a first station of the
plurality of stations is configured to use beamforming weights
associated with a spatial stream to a second station of the
plurality of stations.
20. The communications device of claim 15, further comprising:
means for decompressing the compressed feedback matrices based at
least in part on angles associated with the compressed feedback
matrix for each of the plurality of stations.
21. (canceled)
22. A non-transitory computer-readable medium comprising
computer-readable code that, when executed, causes a device to:
receive compressed beamforming information from each of a plurality
of stations, the compressed beamforming information including a
feedback signal-to-noise ratio (SNR) value and compressed feedback
matrix; determine a multi-user signal-to-interference-plus noise
ratio (SINR) metric for each of the plurality of stations based at
least in part on the received feedback SNR values and the received
compressed feedback matrices; and set a transmission rate for each
of the plurality of stations based at least in part on the
determined multi-user SINR metrics.
23. The non-transitory computer-readable medium of claim 22,
wherein the computer-readable code that, when executed, further
causes the device to: form a multi-user transmission group from the
plurality of stations based at least in part on the determined
multi-user SINR metrics.
24. The non-transitory computer-readable medium of claim 22,
wherein the computer-readable code that, when executed, causes the
device to determine the multi-user SINR metric for each of the
plurality of stations, further cause the device to: determine a
beamforming steering matrix based at least in part on the received
SNR values and received compressed feedback matrices; and determine
the multi-user SINR metric for each of the plurality of stations
based at least in part on the determined beamforming steering
matrix.
25. The non-transitory computer-readable medium of claim 24,
wherein the computer-readable code that, when executed, further
causes the device to: perform a subsequent channel sounding
procedure prior to performing a multi-user transmission to a
multi-user transmission group formed based at least in part on an
initial channel sounding procedure, the subsequent channel sounding
procedure using the determined beamforming steering matrix.
26. The non-transitory computer-readable medium of claim 22,
wherein the computer-readable code that, when executed, causes the
device to determine the multi-user SINR metric for each of the
plurality of stations, further cause the device to determine the
multi-user SINR metric for a first station of the plurality of
stations comprises using beamforming weights associated with a
spatial stream to a second station of the plurality of
stations.
27. The non-transitory computer-readable medium of claim 22,
wherein the computer-readable code that, when executed, further
causes the device to: decompress the compressed feedback matrices
based at least in part on angles associated with the compressed
feedback matrix for each of the plurality of stations.
28. (canceled)
Description
BACKGROUND
[0001] Field of the Disclosure
[0002] The present disclosure, for example, relates to wireless
communication systems, and more particularly to techniques for
using compressed beamforming information for optimizing
multiple-input multiple-output (MIMO) operations.
[0003] Description of Related Art
[0004] Wireless communication systems are widely deployed to
provide various types of communication content such as voice,
video, packet data, messaging, broadcast, and so on. These systems
may be multiple-access systems capable of supporting communication
with multiple users by sharing the available system resources
(e.g., time, frequency, and power). A wireless local area network
(WLAN) is an example of a multiple-access system and are widely
deployed and used. Other examples of multiple-access systems may
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.
[0005] A WLAN, such as a Wi-Fi (IEEE 802.11) network, may include
an access point (AP) that may communicate with one or more stations
(STAs) or mobile devices. In some cases, the AP may communicate
with more than one STA simultaneously in a multi-user MIMO
(MU-MIMO) transmission. The AP may assign a group of STAs to a
MU-MIMO group and send a MIMO transmission to the group of STAs
assigned to the MU-MIMO group. With opportunistic scheduling, the
AP may change the STAs assigned to the MU-MIMO group during every
sounding period based on, for example, availability of traffic,
modulation and coding scheme (MCS) compatibility, etc. However,
when a STA is grouped with other STAs in a MU-MIMO groups that are
incompatible (e.g., where each STA in the MU-MIMO group has high
channel correlation), the packet error rate (PER) for the MU-MIMO
group may increase for the group due to inter-user
interference.
SUMMARY
[0006] The present description discloses techniques for using
compressed beamforming information for optimizing MIMO operations.
According to these techniques, a wireless communication device
(e.g., an AP or like device) estimates an MU
signal-to-interference-plus-noise (SINR) metric for each STA in a
candidate MU group. The MU SINR metric for each STA represents an
estimate of the SINR that the STA would receive if the wireless
communication device were to transmit a MIMO transmission to the
candidate MU group. In this regard, expected interference
associated with the MIMO transmission to the other STAs of the
candidate MU group is determined and factored into the MU SINR
metric for a particular STA.
[0007] For example, an AP performs a channel sounding procedure and
receives compressed beamforming information from a number of STAs
(e.g., two through eight STAs in some implementations). The
compressed beamforming information associated with each STA
responding to the channel sounding includes a feedback
signal-to-noise ratio (SNR) value and a compressed feedback matrix.
The AP selects some or all of the number of STAs as a candidate MU
group and determines an MU SINR metric for each STA in the
candidate MU group. In some cases, the AP selects multiple
combinations of the number of STAs (e.g., each permutation of a
candidate MU-2, MU-3, and MU-4 groups or some subset of the
permutations thereof) and determines the MU SINR metrics for the
STAs in each of the candidate MU groups. The AP forms an MU
transmission group based at least in part on the determined
multi-user SINR metrics of the STAs in the candidate MU
group(s).
[0008] The MU SINR metric for a particular STA is based at least in
part on the received feedback SNR values and the received
compressed feedback matrices associated with the STAs in a
candidate MU group. For example, the MU SINR metric for a first STA
in the candidate MU group is determined based in part using
beamforming weights associated with the spatial stream(s) (and the
estimated interference caused therefrom) intended for transmission
to the other STA(s) of the candidate MU group. Thus, a particular
STA can have different MU SINR metrics based on a determination of
two different candidate MU groups, each including that particular
STA. In some examples, the AP determines a beamforming steering
matrix associated with a candidate MU group. The beamforming
steering matrix is based at least in part on the received SNR
values and received compressed feedback matrices associated with
the STAs in the candidate MU group. The multi-user SINR metric for
each STA is, in turn, determined based at least in part on the
determined beamforming steering matrix associated with the
candidate MU group.
[0009] In some implementations, the AP performs a subsequent
channel sounding procedure using the beamforming steering matrix
determined from the compressed beamforming information
corresponding to the initial sounding procedure. The compressed
beamforming information received by the AP in response to the
subsequent channel sounding procedure is used to validate and/or
further refine the MU SINR metrics of the STAs in the candidate MU
group from which the beamforming steering matrix was
determined.
[0010] A method for wireless communication is described. In some
examples, the method includes receiving, by a first wireless
device, compressed beamforming information from each of a plurality
of stations, the compressed beamforming information including a
feedback SNR value and compressed feedback matrix, and determining
a multi-user SINR metric for each of the plurality of stations
based at least in part on the received feedback SNR values and the
received compressed feedback matrices.
[0011] A communication device is described. In some example, the
communication device includes a transceiver to receive compressed
beamforming information from each of a plurality of stations, the
compressed beamforming information including a feedback SNR value
and compressed feedback matrix, a multi-user SINR estimator to
determine a multi-user SINR metric for each of the plurality of
stations based at least in part on the received feedback SNR values
and the received compressed feedback matrices.
[0012] Another communication device includes means for receiving
compressed beamforming information from each of a plurality of
stations, the compressed beamforming information including a
feedback SNR value and compressed feedback matrix, and means for
determining a multi-user SINR metric for each of the plurality of
stations based at least in part on the received feedback SNR values
and the received compressed feedback matrices.
[0013] A non-transitory computer-readable medium is described. The
non-transitory computer-readable medium includes computer-readable
code that, when executed, causes a device to receive compressed
beamforming information from each of a plurality of stations, the
compressed beamforming information including a feedback SNR value
and compressed feedback matrix, and determine a multi-user SINR
metric for each of the plurality of stations based at least in part
on the received feedback SNR values and the received compressed
feedback matrices.
[0014] Regarding the above-described method, communication devices,
and non-transitory computer-readable medium, a multi-user
transmission group can be formed from the plurality of stations
based at least in part on the determined multi-user SINR
metrics.
[0015] Determining the multi-user SINR metric for each of the
plurality of stations can further comprise determining a
beamforming steering matrix based at least in part on the received
SNR values and received compressed feedback matrices, and
determining the multi-user SINR metric for each of the plurality of
stations based at least in part on the determined beamforming
steering matrix. A subsequent channel sounding procedure can be
performed using the determined beamforming steering matrix.
[0016] Determining the multi-user SINR metric for a first station
of the plurality of stations can include using beamforming weights
associated with a spatial stream to a second station of the
plurality of stations.
[0017] The compressed feedback matrices can be decompressed based
at least in part on angles associated with the compressed feedback
matrix for each of the plurality of stations.
[0018] An MCS can be set for each of the plurality of stations
based at least in part on the determined multi-user SINR
metrics
[0019] Further scope of the applicability of the described systems,
methods, devices, or computer-readable media will become apparent
from the following detailed description, claims, and drawings. The
detailed description and specific examples are given by way of
illustration only, and various changes and modifications within the
scope of the description will become apparent to those skilled in
the art.
BRIEF DESCRIPTION OF THE DRAWINGS
[0020] A further understanding of the nature and advantages of the
present invention may be realized by reference to the following
drawings. In the appended figures, similar components or features
may have the same reference label. Further, various components of
the same type may be distinguished by following the reference label
by a dash and a second label that distinguishes among the similar
components. If only the first reference label is used in the
specification, the description is applicable to any one of the
similar components having the same first reference label
irrespective of the second reference label.
[0021] FIG. 1 illustrates an example of a wireless communication
system, such as a WLAN, that supports using compressed beamforming
information for optimizing MIMO operations in accordance with
various aspects of the present disclosure;
[0022] FIG. 2 illustrates an example wireless communications
scenario in which a beamformer wireless device determines an MU
SINR metric associated with a beamformee wireless device in
accordance with various aspects of the present disclosure;
[0023] FIGS. 3A-3C show block diagrams of examples of APs receiving
compressed beamforming information from STAs and using the received
compressed beamforming information for optimizing MIMO operations
in accordance with various aspects of the present disclosure;
[0024] FIGS. 4A and 4B show block diagrams of examples of an AP
that supports using compressed beamforming information for
optimizing MIMO operations in accordance with various aspects of
the present disclosure; and
[0025] FIG. 5 shows a flow chart that illustrate examples of
methods for using compressed beamforming information for optimizing
MIMO operations in accordance with various aspects of the present
disclosure.
DETAILED DESCRIPTION
[0026] According to aspects of the present disclosure, a wireless
communication device, such as an access point (AP) utilizes
techniques for using compressed beamforming information for
optimizing multiple-input multiple-output (MIMO) operations. The AP
estimates a multi-user (MU) signal-to-interference-plus-noise
(SINR) metric for each station (STA) in a candidate MU group and
uses the MU SINR metrics with respect to various MIMO operations.
The AP determines the MU SINR metric a particular STA based at
least in part on compressed beamforming information associated with
each STA in the candidate MU group.
[0027] The compressed beamforming information used by the AP to
determine the MU SINR metrics includes feedback signal-to-noise
ratio (SNR) values and compressed feedback matrices. An MU SINR
metric for a particular STA is based at least in part on the
received feedback SNR values and the received compressed feedback
matrices associated with the STAs in a candidate MU group. The AP
decompresses the compressed feedback matrices based at least in
part on angles (e.g., phi .PHI. and psi .PSI. angles) associated
with the rows and columns of the compressed feedback matrix to
obtain a feedback matrix for each STA.
[0028] With the feedback matrix for each STA in a candidate MU
group, the AP determines a beamforming steering matrix associated
with the candidate MU group in accordance with some
implementations. The beamforming steering matrix is based at least
in part on the received SNR values and received compressed feedback
matrices, which have been decompressed to obtain feedback matrices
of the STAs in the candidate MU group. The multi-user SINR metric
for each STA is, in turn, determined based at least in part on the
determined beamforming steering matrix associated with the
candidate MU group.
[0029] The MU SINR metrics for the STAs provide the AP with
estimations of the different levels of channel correlation and
associated inter-user interference that a particular STA may
experience if that particular STA were to be included in various
possible MIMO transmission groupings. As such, the AP forms
efficient MU groups of STAs for MIMO transmissions as well as
accurately determines a proper modulation and coding scheme (MCS)
for each STA in the corresponding MU transmission group.
[0030] By contrast, certain conventional APs solely utilize packet
error rate (PER) history to decide the MCS to be utilized for a STA
in a MIMO group. However, if a STA joins a poor MU group (e.g.,
having large channel correlation and inter-user interference during
the MIMO transmission), the resulting PER for that transmission
occurrence can significantly impact the PER history and improperly
lower MCS for that STA. If that STA then joins a good MU group
(e.g., having small channel correlation and negligible inter-user
interference during the MIMO transmission), that STA can still use
an artificially low MCS based on the PER-based rate adaptation
practices associated with a conventional AP.
[0031] Advantageously, an AP in accordance with aspects of the
present disclosure sets the MCS of a particular STA based at least
in part on the MU SINR metrics associated with candidate MU
group(s). Moreover, the AP determines a correlation metric based at
least in part on the MU SINR metrics. For example, the correlation
metric can be an average, median, or mean distribution of the MU
SINR metrics of the STAs for a candidate MU group. As such, the AP
uses the correlation metric to determine whether the candidate MU
group is an efficient MIMO transmission and whether to remove one
or more STAs from the candidate MU group. Correlation metrics
relating to multiple candidate transmission groups are analyzed by
the AP to detect changes and patterns associated with channel
correlations among the STAs and form efficient MU transmission
groups. In this regard, the AP uses the MU SINR metrics and
correlation metrics to optimize MCS rate adaptation, MU grouping of
STAs, MU transmission group ranking and scheduling, etc.
[0032] The following description provides examples, and is not
limiting of the scope, applicability, or examples set forth in the
claims. Changes may be made in the function and arrangement of
elements discussed without departing from the scope of the
disclosure. Various examples may omit, substitute, or add various
procedures or components as appropriate. For instance, the methods
described may be performed in an order different from that
described, and various steps may be added, omitted, or combined.
Also, features described with respect to some examples may be
combined in other examples.
[0033] Referring first to FIG. 1, a block diagram illustrates an
example of a wireless local area network (WLAN) 100 in accordance
with various aspects of the present disclosure. The WLAN 100
includes an access point (AP) 105 and STAs 110 labeled as STA-1
through STA-7. The STAs 110 can be mobile handsets, tablet
computers, personal digital assistants (PDAs), other handheld
devices, netbooks, notebook computers, tablet computers, laptops,
desktop computers, display devices (e.g., TVs, computer monitors,
etc.), printers, etc. While only one AP 105 is illustrated, the
WLAN 100 can alternatively have multiple APs 105. STAs 110, can
also be referred to as a mobile stations (MS), mobile devices,
access terminals (ATs), user equipment (UEs), subscriber stations
(SSs), or subscriber units. The STAs 110 associate and communicate
with the AP 105 via a communication link 115. Each AP 105 has a
coverage area 125 such that STAs 110 within that area are within
range of the AP 105. The STAs 110 are dispersed throughout the
coverage area 125. Each STA 110 may be stationary or mobile.
Additionally, each AP 105 and STA 110 can have multiple
antennas.
[0034] While, the STAs 110 are capable of communicating with each
other through the AP 105 using communication links 115, STAs 110
can also communicate directly with each other via direct wireless
communication links 120. Direct wireless communication links can
occur between STAs 110 regardless of whether any of the STAs is
connected to an AP 105. As such, a STA 110 or like device can
include techniques for using compressed beamforming information for
optimizing MIMO operations as described herein with respect to an
AP 105.
[0035] The STAs 110 and AP 105 shown in FIG. 1 communicate
according to the WLAN radio and baseband protocol including
physical (PHY) and medium access control (MAC) layers from IEEE
802.11, and its various versions including, but not limited to,
802.11b, 802.11g, 802.11a, 802.11n, 802.11ac, 802.11ad, 802.11ah,
802.11z, etc. Thus, WLAN 100 implements a contention-based protocol
that allows a number of devices (e.g., STAs 110 and APs 105) to
share the same wireless medium (e.g., a channel) without
pre-coordination. To prevent several devices from transmitting over
the channel at the same time each device in a BSS operates
according to certain procedures that structure and organize medium
access, thereby mitigating interference between the devices.
[0036] In WLAN 100, AP 105 utilizes techniques for using compressed
beamforming information (e.g., very high throughput (VHT)
compressed beamforming (CBF) report information) for optimizing
MIMO operations. AP 105 utilizes certain transmission techniques
such as MIMO and MU-MIMO. A MIMO communication typically involves
multiple transmitter antennas (e.g., at an AP 105) sending a signal
or signals to multiple receive antennas (e.g., at a STA 110). Each
transmitting antenna transmits independent data (or spatial)
streams to increase spatial diversity and the likelihood successful
signal reception. In other words, MIMO techniques use multiple
antennas on AP 105 and/or multiple antennas on a STA 110 in the
coverage area 125 to take advantage of multipath environments to
transmit multiple data streams.
[0037] AP 105 also implements MU-MIMO transmissions in which AP 105
simultaneously transmits independent data streams to multiple STAs
110. In one example of an MU-N transmission (e.g., MU-2, MU-3,
MU-4, etc.), an AP 105 simultaneously transmits signals to N STAs.
Thus, when AP 105 has traffic for many STAs 110, the AP 105
increases network throughput by aggregating individual streams for
each STA 110 in the group into a single MU-MIMO transmission.
[0038] In implementing various MU-MIMO techniques and operations,
AP 105 (e.g., beamformer device) relies on multi-user channel
sounding procedures performed with the STAs 110 (e.g., beamformee
devices) in the coverage area 125 to determine how to radiate
energy in a preferred direction. AP 105 sounds the channel by
transmitting null data packet announcement (NDPA) frames and null
data packet (NDP) frames to a number of STAs 110 such as STA-1,
STA-2, STA-3, STA-4, STA-5, and STA-6. AP 105 has knowledge that
STA-7 does not support MU-MIMO operations, for instance, and does
not include STA-7 in the multi-user channel sounding procedure.
[0039] AP 105 also transmits a beamforming report poll frame after
the NDPA and NDP frames to coordinate and collect responses from
the number of STAs 110. Each of the STAs 110 responds in turn with
a compressed beamforming action frame (e.g., a VHT CBF frame) for
transmitting VHT CBF feedback to AP 105. The VHT CBF feedback
contains the VHT CBF report information, portions of which the AP
105 uses to determine MU SINR metrics for the number of STAs
110.
[0040] The VHT CBF report information includes feedback information
such as compressed beamforming feedback matrix V compressed in the
form of angles (i.e., phi .PHI. and psi .PSI. angles) that are
quantized according to a standard (e.g., IEEE 802.11ac). The VHT
CBF report information also includes a feedback signal-to-noise
ratio (SNR) value (e.g., an Average SNR of Space-Time Stream Nc,
where Nc is the number of columns in the compressed beamforming
feedback matrix V). Each SNR value per tone in stream i (before
being averaged) corresponds to the SNR associated with the column i
of the beamforming feedback matrix V determined at the STA 110. The
feedback SNR values are based on the NDP frames in the channel
sounding procedure, and therefore each of these feedback SNR values
generally corresponds to a SNR that a particular STA 110 may
experience in a single-user (SU) transmission from AP 105 to the
particular STA 110.
[0041] AP 105 collects the VHT CBF report information from each STA
110 and uses the feedback information to determine the SINR metrics
and beamforming steering matrices in some examples. It is to be
understood that the multi-user channel sounding procedures
described herein are provided as non-limiting examples. Other
channel sounding procedures for obtaining compressed beamforming
information can be used for optimizing MIMO operations as would be
apparent to a skilled person given the benefit of the present
disclosure.
[0042] FIG. 2 illustrates an example wireless communications
scenario 200 in which a beamformer wireless device determines an MU
SINR metric associated with a beamformee wireless device in
accordance with various aspects of the present disclosure. The
example wireless communications scenario 200 shown in FIG. 2 is
illustrated with respect to AP 105-a and STA 110-a, which are
respective examples of the AP 105 and STAs 110 of FIG. 1. In this
example, AP 105-a has received VHT CBF report information from each
STA 110, STA-1 (depicted as STA 110-a in FIG. 2), STA-2, STA-3,
STA-4, STA-5, and STA-6 , as described with respect to FIG. 1. AP
105-a has determined to analyze a candidate MU-MIMO group
consisting of STA-1, STA-2, and STA-3.
[0043] In the example wireless communications scenario 200, the
number of user is 3, the number of space-time streams (N.sub.STS)
per user is 1, the number of transmit antennas (N.sub.tx) at AP
105-a is 4, and the number of receive antennas (N.sub.rx) at STA-1
110-a is 1. Symbols propagate from transmit antennas 222, 224, 226,
228 of AP 105-a to receive antenna 232 of STA-1 110-a by way of
four separate radio paths: channel element h1,1 from first transmit
antenna 222 to receive antenna 232; channel element h1,2 from
second transmit antenna 224 to receive antenna 232; channel element
h1,3 from third transmit antenna 226 to receive antenna 232; and
channel element h1,4 from fourth transmit antenna 228 to receive
antenna 232. The received signals can be expressed as follows:
[ y 1 y 2 y 3 ] = H W [ x 1 x 2 x 3 ] + n ##EQU00001##
[0044] where x.sub.1, x.sub.2, and x.sub.3 are the signals for
STA-1, STA-2, and STA-3, respectively, sent from the transmit
antennas 222, 224, 226, 228 of AP 105-a; y.sub.1, y.sub.2, and
y.sub.3 are the signals that arrive at the receive antenna 232 of
STA-1 110-a, the receive antenna of STA-2, and the receive antenna
of STA-3, respectively. H expresses the way in which the
transmitted symbols are attenuated, phase-shifted, distorted, etc.
as the symbols travel from the transmit antennas to the receive
antennas. W represents the beamforming steering matrix to transmit
signals x.sub.1, x.sub.2, and x.sub.3 as determined using the
compressed beamforming information received by AP 105-a during the
channel sounding procedure, and n represents the received noise and
interference.
[0045] Thus, y.sub.1 can be expressed as follows:
y 1 = [ - h 1 - ] [ w 1 w 2 w 3 ] [ x 1 x 2 x 3 ] + n = h 1 w 1 x 1
+ h 1 w 2 x 2 + h 1 w 3 x 3 + n ##EQU00002##
[0046] The expected value is the estimate of the transmitted signal
x.sub.1 as would be receive by STA-1 110-a, and can be determined
as follows:
= ( h 1 w 1 ) * y 1 h 1 w 1 2 ##EQU00003##
[0047] while the mean square error (MSE) can be expressed as
follows:
MSE={{circumflex over (x)}-x) ({circumflex over (x)}-x)*}
[0048] Thus, the mean square error can be written as follows:
M S E = s 1 2 3 v 1 * w 2 2 + s 1 2 3 v 1 * w 3 2 + 1 s 1 2 v 1 * w
1 2 ##EQU00004##
[0049] where s.sub.1 is the feedback SNR value v.sub.1* is the
decompressed or decomposed feedback matrix from compressed
beamforming feedback matrix V from the compressed beamforming
information provided by STA-1 during the channel sounding
procedure. The beamforming steering matrix components (e.g.,
beamforming weights) w.sub.1,w.sub.2, and w.sub.3 of beamforming
steering matrix Ware likewise determined using the compressed
beamforming information provided by STA-1, STA-2, and STA-3 during
the channel sounding procedure.
[0050] AP 105-a can then determine an MU SINR metric as would be
observed by STA-1 110-a if AP 105-a were to transmit an MU-MIMO
transmission to the MU-MIMO group consisting of STA-1, STA-2, and
STA-3. The MU SNR metric (SINR.sub.est) associated with STA-1 can
be determined as follows:
SINR est = { x 1 2 } M S E = s 1 2 3 v 1 * w 1 2 s 1 2 3 ( v 1 * w
2 2 + v 1 * w 3 2 ) + 1 ##EQU00005##
[0051] Similar MU SINR metrics can be determined by AP 105-a as
would be observed by each of STA-2 and STA-3. For example, the MU
SINR metric as would be observed by STA-2 if AP 105-a were to
transmit an MU-MIMO transmission to the MU-MIMO group consisting of
STA-1, STA-2, and STA-3 can be determined as follows:
SINR est = s 2 2 3 v 2 * w 2 2 s 2 2 3 ( v 2 * w 1 2 + v 2 * w 3 2
) + 1 ##EQU00006##
[0052] The MU SINR metric as would be observed by STA-3 if AP 105-a
were to transmit an MU-MIMO transmission to the MU-MIMO group
consisting of STA-1, STA-2, and STA-3 can be determined as
follows:
SINR est = s 3 2 3 v 3 * w 3 2 s 3 2 3 ( v 3 * w 1 2 + v 3 * w 2 2
) + 1 ##EQU00007##
[0053] Characteristics of the disclosed equations for the MU SINR
metrics (SINR.sub.est) and similar techniques as would be apparent
to a skilled person given the benefit of the present disclosure
include, but are not limited to: using beamforming weights
associated with a spatial stream to other STAs (e.g., a second STA,
a third STA, a fourth STA, etc.) to determine the MU SINR metric
for a first STA; using interference estimates associated with
spatial streams from other STAs in MU-MIMO transmission at a
detriment to the MU SINR metric of a first STA; and using a
single-user SNR value of a first STA with interference estimates of
other STAs to determine the MU SINR metric of the first STA.
[0054] Moreover, in addition to the actual values calculated using
the disclosed equations, some examples of the MU SINR metric
include weightings of the various components and/or approximations
as determined by AP 105-a associated with various wireless
environments and/or operational conditions.
[0055] In some embodiments, AP 105-a does not calculate the
beamforming steering matrix W for the purpose of analyzing
candidate MU-MIMO groups. Instead, AP 105-a utilizes a default
value or a historical value (e.g., derived from the same or similar
STAs under like conditions) for the beamforming steering matrix
Wand beamforming steering matrix components w.sub.1, w.sub.2, and
w.sub.3. For example, AP 105-a determines that an approximation of
beamforming steering matrix W can be used based at least in part on
a comparison of the received compressed beamforming information
corresponding to a present MU SINR metric determination with
previously received compressed beamforming information. As such,
the beamforming steering matrix W determined under comparable
feedback information or used for actual MU-MIMO transmission of the
same or similar MU-MIMO groups of STAs can be used as an
approximation of beamforming steering matrix W for the MU SINR
metric calculations. In yet other embodiments, AP 105-a entirely
eliminates the beamforming steering matrix Wand beamforming
steering matrix components w.sub.1, w.sub.2, and w.sub.3 from for
the MU SINR metric calculations, for example, by directly using the
channel feedback values, s.sub.1v.sub.1, s.sub.2v.sub.2, and
s.sub.3v.sub.3, respectively, in their places in the described
calculations. Such embodiments approximating or eliminating the
beamforming steering matrix W from the MU SINR metric calculations
can be used, for example, when temporary computational constraints
exist within AP 105-a (e.g., in certain instances where computing
an minimum mean square error (MMSE)-optimized beamforming steering
matrix W is costly and/or too time intensive).
[0056] Example wireless communications scenario 200 represents one
of many combinations of STAs 110 the AP 105-a may analyze for
determining effective MU-MIMO transmission groups with which to
transmit data to the number of STAs 110. In one example, AP 105-a
determines MU SINR metrics and analyzes candidate MU-MIMO groups
comprised of STA-2 and STA-3 as a possible MU-2 group, STA-1,
STA-5, and STA-6 as a possible MU-3 group, and STA-3, STA-4, STA-5,
and STA-6 as a possible MU-4 group.
[0057] In this example, AP 105-a determines a correlation metric
among the MU SINR metrics of STA-3, STA-4, STA-5, and STA-6 as the
candidate MU-4 group, and determines the MU SINR metric of STA-5 is
significantly lower (e.g., by one or two standard deviations from
the median of all SINR metrics of the candidate MU-4 group). As
such, AP 105-a removes STA-5 from the candidate MU-4 group thereby
reducing the size of the candidate
[0058] MU-MIMO group to a new candidate MU-3 group. AP 105-a now
determines MU SINR metrics of STA-3, STA-4, and STA-6 as the new
candidate MU-3 group, and determines the MU SINR metrics of each of
STA-3, STA-4, and STA-6 have increased over their respective MU
SINR metrics in the former candidate MU-4 group that included
STA-5. AP 110-a then blacklists STA-5 from MU-MIMO transmission
groupings with any of STA-3, STA-4, and STA-6 for a predetermined
period of time (e.g., 500 ms, 5 second, 30 seconds, 2 minutes, 5
minutes, etc.).
[0059] In this regard, a goal of analyzing various candidate
MU-MIMO groups is to determine channel correlation patterns among
the STAs 110 and identity groups of STAs 110 that exhibit good
uncorrelated channel characteristics so as to form efficient
MU-MIMO transmission groups. In this instance, each STA 110 in an
efficient MU-MIMO transmission group exhibits a high MU SINR
metric. The high MU SINR metrics of the STAs in such an efficient
MU-MIMO transmission group are also correlated to high achievable
high MCS rates.
[0060] FIG. 3A shows a block diagram 300-a of example of an AP
receiving compressed beamforming information from STAs and using
the received compressed beamforming information for optimizing MIMO
operations in accordance with various aspects of the present
disclosure. The example block diagram 300-a shown in FIG. 3A is
illustrated with respect to AP 105-b and STAs 110-b, 110-c, 110-d,
which are respective examples of the AP 105 and STAs 110 of FIGS. 1
and 2.
[0061] Each of STA-1 110-b, STA-2 110-c, and STA-n 110-d transmits
compressed beamforming information to AP 105-b. MU SINR estimator
340 of AP 105-b processes the received compressed beamforming
information to determine a MU SINR metric for each of STA-1 110-b,
STA-2 110-c, and STA-n 110-d as a candidate MU-MIMO group. The MU
SINR metric for each of STA-1 110-b, STA-2 110-c, and STA-n 110-d
is determined as an estimate of the SINR that the respective STA
would receive if AP 105-c were to transmit a MU-MIMO transmission
to the candidate MU-MIMO group of STA STA-1 110-b, STA-2 110-c, and
STA-n 110-d. As such, the interference associated with the
calculated MU SINR metric of a particular STA 110 relates to
interference that would be caused by the packets simultaneously
transmitted to the other stations in a MU-MIMO transmission.
[0062] In some cases, MU SINR estimator 340 of AP 105-b also
determines an additional MU SINR metric for each of STA-1 110-b,
STA-2 110-c, and STA-n 110-d using different candidate MU-MIMO
groups. These different candidate MU-MIMO groups include various
MU-2, MU-3, MU-4, etc. group combinations of STA-1 110-b, STA-2
110-c, and STA-n 110-d,
[0063] In this example, MU SINR estimator 340 does not use a
beamforming steering matrix W to calculate MU SINR metrics. For
example, a null value, default value, or historical value for
beamforming steering matrix W (e.g., as previously determined by
beamforming steering matrix determiner 350) is used in the
calculations of the MU SINR metrics.
[0064] Additionally, MU SINR estimator 340 of AP 105-b is
configured to perform single-user MIMO operations in some
embodiments. For example, single-user MIMO transmission parameters
(N.sub.ss, MCS) for a STA 110 are based on feedback information
contained in a CBF report received from that STA 110. For each
spatial stream, AP 105-b maps the received SNR value to a bits per
second (bps) value using a constrained capacity formula such as C
=max(log(l+SNR), 8). In implementations where AP 105-b must
transmit using a single MCS to all spatial streams, AP 105-b
selects a minimum MCS over selection of multiple spatial streams.
AP 105-b can choose to transmit at N.sub.ss=1, . . . ,
N.sub.ss.sub._.sub.total, and selects N.sub.ss such that a total
throughput rate is maximized among the combinations of single-user
MIMO transmission parameters (N.sub.ss, MCS) for the STA 110.
[0065] When AP 105-b determines an MU-MIMO transmission group based
at least in part on the determined MU SINR metrics, a beamforming
steering matrix W is determined by beamforming steering matrix
determiner 350, and the MU-MIMO transmission is performed by
transmitter 360.
[0066] FIG. 3B shows a block diagram 300-b of example of an AP
receiving compressed beamforming information from STAs and using
the received compressed beamforming information for optimizing MIMO
operations in accordance with various aspects of the present
disclosure. The example block diagram 300-b shown in FIG. 3B is
illustrated with respect to AP 105-c and STAs 110-e, 110-f, 110-g,
which are respective examples of the AP 105 and STAs 110 of FIGS. 1
2, and 3A.
[0067] Each of STA-1 110-e, STA-2 110-f, and STA-n 110-g transmits
compressed beamforming information to AP 105-c. Decompressor(s) 325
of AP 105-c decompresses the received compressed beamforming
information. For example, decompressor 325 of AP 105-c decompresses
compressed feedback matrices based at least in part on angles
(e.g., phi .PHI. and psi .PSI. angles) associated with the rows and
columns of each compressed feedback matrix V to obtain a
decompressed beamforming matrix (e.g., feedback matrix V*) for each
of STA-1 110-e, STA-2 110-f, and STA-n 110-g.
[0068] MU SINR estimator 340-a of AP 105-c processes decompresses
compressed feedback matrices and other received compressed
beamforming information to determine a MU SINR metric for each of
STA-1 110-e, STA-2 110-f, and STA-n 110-g as a candidate MU-MIMO
group. In some cases, MU SINR estimator 340-a of AP 105-c also
determines an additional MU SINR metric for each of STA-1 110-e,
STA-2 110-f, and STA-n 110-g using different candidate MU-MIMO
groups. These different candidate MU-MIMO groups include various
MU-2, MU-3, MU-4, etc. group combinations of STA-1 110-e, STA-2
110-e, and STA-n 110-g.
[0069] When AP 105-c determines an MU-MIMO transmission group based
at least in part on the determined MU SINR metrics, a beamforming
steering matrix W is determined by beamforming steering matrix
determiner 350-a, and the MU-MIMO transmission is performed by
transmitter 360-a.
[0070] FIG. 3C shows a block diagram 300-c of example of an AP
receiving compressed beamforming information from STAs and using
the received compressed beamforming information for optimizing MIMO
operations in accordance with various aspects of the present
disclosure. The example block diagram 300-c shown in FIG. 3A is
illustrated with respect to AP 105-d and STAs 110-h , 110-i, 110-j,
which are respective examples of the AP 105 and STAs 110 of FIGS.
1, 2, 3A, and 3B.
[0071] Each of STA-1 110-h , STA-2 110-i, and STA-n 110-j, trasmits
compressed beamforming information to AP 105-d. Decompressor(s)
325-a of AP 105-decompresses the received compressed beamforming
information. For example, decompressor 325-a of AP 105-d
decompresses compressed feedback matrices based at least in part on
angles (e.g., phi .PHI. and psi .PSI. angles) associated with the
rows and columns of each compressed feedback matrix V to obtain a
decompressed beamforming matrix (e.g., feedback matrix V*) for each
of STA-1 110-h , STA-2 110-i , and STA-n 110-j. In doing so,
decompressor(s) 325-a of AP 105-d decompress the received
compressed feedback matrices (e.g., regenerate the feedback
matrices V*) by using a matrix multiplication operation called a
Givens rotation.
[0072] Computation/interpolation blocks 330 of AP 105-d receive the
decompresses compressed feedback matrices and other received
compressed beamforming information (e.g., feedback SNR values and
feedback matrices V*). The computation/interpolation blocks 330
perform various, filtering, coding, and phase-shifting operations
and forwards the feedback information to both the MU SINR estimator
340-b and stacker 335. Stacker 335 stacks the feedback SNR values
and feedback matrices V* and forwards the results to beamforming
steering matrix determiner 350-b. Beamforming steering matrix
determiner 350-b determines beamforming steering matrix W
associated with a MU-MIMO transmission of STA-1 110-h , STA-2 110-i
, and STA-n 110-j. Beamforming steering matrix determiner 350-b
provides the beamforming steering matrix W to MU SINR estimator
340-b, which in turn determines a MU SINR metric for each of STA-1
110-h , STA-2 110-i , and STA-n 110-j based at least in part on the
beamforming steering matrix W.
[0073] When AP 105-d determines the MU-MIMO transmission group
based at least in part on the determined MU SINR metrics, the
corresponding beamforming steering matrix W of the selected MU-MIMO
transmission group is forwarded to combiner 355. Combiner 355
performs cyclic shift diversity operations, and the MU-MIMO
transmission is performed by transmitter 360-b.
[0074] It is to be appreciated that the block diagrams 300-a,
300-b, 300-c of FIGS. 3A-3C are some examples of APs 105 that use
compressed beamforming information to optimize MIMO operations, and
other wireless communication devices can implement the techniques
described herein. Wireless communication devices (including APs
105) determine MU SINR metrics and correlation metrics to optimize
MCS rate adaptation, MU grouping of STAs, MU transmission group
ranking and scheduling, etc. as well as other MIMO operations.
[0075] FIG. 4A shows a block diagram 400-a of an example AP 105-e
that supports using compressed beamforming information for
optimizing MIMO operations in accordance with various aspects of
the present disclosure, and with respect to FIGS. 1-3C. The AP
105-e includes a processor 405, a memory 410, one or more
transceivers 420, one or more antennas 425, an MCS manager 440, a
MU grouping manager 435, a decompressor 325-b, a beamforming
steering matrix determiner 350-c, and a MU SINR estimator 340-c.
The processor 405, memory 410, transceiver(s) 420, MCS manager 440,
MU grouping manager 435, decompressor 325-b, beamforming steering
matrix determiner 350-c, and MU SINR estimator 340-c are
communicatively coupled with a bus 430, which enables communication
between these components. The antenna(s) 425 are communicatively
coupled with the transceiver(s) 420.
[0076] The processor 405 is an intelligent hardware device, such as
a central processing unit (CPU), a microcontroller, an
application-specific integrated circuit (ASIC), etc. The processor
405 processes information received through the transceiver(s) 420
and information to be sent to the transceiver(s) 420 for
transmission through the antenna(s) 425.
[0077] The memory 410 stores computer-readable, computer-executable
software (SW) code 415 containing instructions that, when executed,
cause the processor 405 or another one of the components of the AP
105-e to perform various functions described herein, for example,
receiving compressed beamforming information for a number of STAs
110 and determining MU SINR metrics and correlation metric(s)
associated with the STAs.
[0078] The transceiver(s) 420 communicate bi-directionally with
other wireless devices, such as stations 110, other APs 105, or
other devices. The transceiver(s) 420 include a modem to modulate
packets and frames and provide the modulated packets to the
antenna(s) 425 for transmission. The modem is additionally used to
demodulate packets received from the antenna(s) 425.
[0079] The MCS manager 440, MU grouping manager 435, decompressor
325-b, beamforming steering matrix determiner 350-c, and MU SINR
estimator 340-cimplement the features described with reference to
FIGS. 1-3C, as further explained below.
[0080] Again, FIG. 4A shows only one possible implementation of a
device executing the features of FIGS. 1-3. While the components of
FIG. 4A are shown as discrete hardware blocks (e.g., ASICs, field
programmable gate arrays (FPGAs), semi-custom integrated circuits,
etc.) for purposes of clarity, it will be understood that each of
the components may also be implemented by multiple hardware blocks
adapted to execute some or all of the applicable features in
hardware. Alternatively, features of two or more of the components
of FIG. 4A may be implemented by a single, consolidated hardware
block. For example, a single transceiver 420 chip may implement the
processor 405, MCS manager 440, MU grouping manager 435,
decompressor 325-b, beamforming steering matrix determiner 350-c,
and MU SNR estimator 340-c.
[0081] In still other examples, the features of each component may
be implemented, in whole or in part, with instructions embodied in
a memory, formatted to be executed by one or more general or
application-specific processors. For example, FIG. 4B shows a block
diagram 400-b of another example of an AP 105-f in which the
features of the MCS manager 440-a, MU grouping manager 435-a,
decompressor 325-c, beamforming steering matrix determiner 350-d,
and MU SINR estimator 340-d are implemented as computer-readable
code stored on memory 410-a and executed by one or more processors
405-a. Other combinations of hardware/software may be used to
perform the features of one or more of the components of FIGS. 4A
and 4B.
[0082] FIG. 5 shows a flow chart that illustrates one example of a
method 500 for using compressed beamforming information for
optimizing MIMO operations in accordance with various aspects of
the present disclosure. Method 500 may be performed by any of the
APs 105 and STAs 110 discussed in the present disclosure, but for
clarity method 500 will be described from the perspective of AP
105-e of FIG. 4A as the beamformer wireless device and the STAs 110
of FIG. 1 and referenced in FIG. 2 as the beamformee wireless
devices. It is to be understood that method 500 is just one example
of techniques for using compressed beamforming information, and the
operations of the method 500 may be rearranged, performed by other
devices and component thereof, and/or otherwise modified such that
other implementations are possible.
[0083] Broadly speaking, the method 500 illustrates a procedure by
which the AP 105-e receives compressed beamforming information from
multiple stations, the compressed beamforming information
containing a feedback SNR value and compressed feedback matrix, and
determines a multi-user SINR metric for each station based at least
in part on the received SNR values and the received compressed
feedback matrices.
[0084] At block 505, transceiver 420 of the AP 105-e performs a
channel sounding procedure. The channel sounding procedure includes
the transmission of a Null Data Packet (NDP) Announcement frame to
identify stations selected as beamformees. The transceiver 420
receives an acknowledgement or other response to the NDP
announcement. The transceiver 420 then transmits a NDP with
containing training fields that are known to the stations.
[0085] At block 510, the transceiver 420 receives compressed
beamforming information from each of a plurality of stations in
response to the NDP. The compressed beamforming information for
each station includes a feedback signal-to-noise ratio (SNR) value
and compressed feedback matrix.
[0086] At block 515, MU SINR estimator 340-c determines a
multi-user signal-to-interference-plus noise ratio (SINR) metric
for each of the beamformee stations based at least in part on the
received feedback SNR values and the received compressed feedback
matrices. The SINR metric is determined according to the principles
described in FIGS. 1-3B. The AP 105-e can use the MU SINR metric
for the stations in a number of ways. According to one option, at
block 520, decompressor 325-b decompresses the compressed feedback
matrix, and at block 525 beamforming steering matrix determiner
350-c determines a beamforming steering matrix from the
decompressed feedback matrix. According to a second option, at
block 530, MU grouping manager 435 forms a MU transmission group
based at least in part on the determined MU SINR metrics. According
to a third option, at block 535 MCS manager 440 sets an MCS for one
or more of the stations based at least in part on the determined MU
SINR metrics.
[0087] At block 540, transceiver 420 performs a subsequent channel
sounding procedure. The subsequent channel sounding procedure is
the same as or substantially similar to the channel sounding
procedure of block 505. At block 545, transceiver 420 receives an
additional set of compressed beamforming information from the
stations selected as beamformees. At block 550, MU-SINR estimator
340-c determines additional MU SINR metrics based at least in part
on the new compressed beamforming information.
[0088] At block 555, MU grouping manager 435 identifies one or more
correlation metrics between stations using the MU SINR metrics from
the first and second sounding procedures. Based at least in part on
the correlation metric(s), at block 560, MU grouping manager 435
forms one or more new MU transmission groups or modifies one or
more existing MU transmission groups. The MU grouping manager 435
takes these actions to group closely correlated stations together.
At block 565, transceiver 420 transmits to an MU transmission group
based at least in part on the determined MU SINR metrics.
[0089] At block 555, AP 105-e transmits a multi-user transmission
group from the plurality of stations based at least in part on the
determined multi-user SINR metrics.
[0090] The detailed description set forth above in connection with
the appended drawings describes examples and does not represent the
only examples that may be implemented or that are within the scope
of the claims. The terms "example" and "exemplary," when used in
this description, mean "serving as an example, instance, or
illustration," and not "preferred" or "advantageous over other
examples." The detailed description includes specific details for
the purpose of providing an understanding of the described
techniques. These techniques, however, may be practiced without
these specific details. In some instances, well-known structures
and apparatuses are shown in block diagram form in order to avoid
obscuring the concepts of the described examples.
[0091] Information and signals may be represented using any of a
variety of different technologies and techniques. For example,
data, instructions, commands, information, signals, bits, symbols,
and chips that may be referenced throughout the above description
may be represented by voltages, currents, electromagnetic waves,
magnetic fields or particles, optical fields or particles, or any
combination thereof.
[0092] The various illustrative blocks and components described in
connection with the disclosure herein may be implemented or
performed with a general-purpose processor, a digital signal
processor (DSP), an ASIC, an FPGA or other programmable logic
device, discrete gate or transistor logic, discrete hardware
components, or any combination thereof designed to perform the
functions described herein. A general-purpose processor may be a
microprocessor, but in the alternative, the processor may be any
conventional processor, controller, microcontroller, or state
machine. A processor may also be implemented as a combination of
computing devices, e.g., a combination of a DSP and a
microprocessor, multiple microprocessors, one or more
microprocessors in conjunction with a DSP core, or any other such
configuration.
[0093] The functions described herein may be implemented in
hardware, software executed by a processor, firmware, or any
combination thereof. If implemented in software executed by a
processor, the functions may be stored on or transmitted over as
one or more instructions or code on a computer-readable medium.
Other examples and implementations are within the scope and spirit
of the disclosure and appended claims. For example, due to the
nature of software, functions described above can be implemented
using software executed by a processor, hardware, firmware,
hardwiring, or combinations of any of these. Features implementing
functions may also be physically located at various positions,
including being distributed such that portions of functions are
implemented at different physical locations. As used herein,
including in the claims, the term "and/or," when used in a list of
two or more items, means that any one of the listed items can be
employed by itself, or any combination of two or more of the listed
items can be employed. For example, if a composition is described
as containing components A, B, and/or C, the composition can
contain A alone; B alone; C alone; A and B in combination; A and C
in combination; B and C in combination; or A, B, and C in
combination. Also, as used herein, including in the claims, "or" as
used in a list of items (for example, a list of items prefaced by a
phrase such as "at least one of" or "one or more of") indicates a
disjunctive list such that, for example, a list of "at least one of
A, B, or C" means A or B or C or AB or AC or BC or ABC (i.e., A and
B and C).
[0094] Computer-readable media includes both computer storage media
and communication media including any medium that facilitates
transfer of a computer program from one place to another. A storage
medium may be any available medium that can be accessed by a
general purpose or special purpose computer. By way of example, and
not limitation, computer-readable media can comprise RAM, ROM,
EEPROM, flash memory, CD-ROM or other optical disk storage,
magnetic disk storage or other magnetic storage devices, or any
other medium that can be used to carry or store desired program
code means in the form of instructions or data structures and that
can be accessed by a general-purpose or special-purpose computer,
or a general-purpose or special-purpose processor. Also, any
connection is properly termed a computer-readable medium. For
example, if the software is transmitted from a website, server, or
other remote source using a coaxial cable, fiber optic cable,
twisted pair, digital subscriber line (DSL), or wireless
technologies such as infrared, radio, and microwave, then the
coaxial cable, fiber optic cable, twisted pair, DSL, or wireless
technologies such as infrared, radio, and microwave are included in
the definition of medium. Disk and disc, as used herein, include
compact disc (CD), laser disc, optical disc, digital versatile disc
(DVD), floppy disk and Blu-ray disc where disks usually reproduce
data magnetically, while discs reproduce data optically with
lasers. Combinations of the above are also included within the
scope of computer-readable media.
[0095] The previous description of the disclosure is provided to
enable a person skilled in the art to make or use the disclosure.
Various modifications to the disclosure will be readily apparent to
those skilled in the art, and the generic principles defined herein
may be applied to other variations without departing from the scope
of the disclosure. Thus, the disclosure is not to be limited to the
examples and designs described herein but is to be accorded the
broadest scope consistent with the principles and novel features
disclosed herein.
* * * * *