IEEE C802.16m-09/2761r1
Project
Title
IEEE 802.16 Broadband Wireless Access Working Group < http://ieee802.org/16 >
Frequency Selectivity of the Beam forming in Sounding based CL MIMO (Section
16.3.7.2.5.7 of the IEEE 802.16m/D3)
2009-12-30 Date
Submitted
Source(s) Alexei Davydov
Tom Harel
Re:
Huaning Niu
Yuan Zhu
Category: LB30b / Area: Chapter 16.3.7
Abstract alexei.davydov@intel.com
The contribution proposes constraints on frequency selectivity of the beam forming in sounding based MIMO
Purpose
Notice
Release
Patent
Policy
To be discussed and adopted by TGm for the 802.16m Advanced Air Interface (Draft 4)
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Alexei Davydov, Huaning Niu, Tom Harel, Yuan Zhu
Intel Corporation
[1] Cong Shen, Michael P. Fitz, “MIMO-OFDM Beamforming for Improved Channel Estimation in 802.11n
WLAN” IEEE 802.11-06/0979r0
[2] J. Sadowsky, Tomoya Yamaura, John Ketchum, ”WWiSE Preambles and MIMO Beamforming?”, IEEE
802.11-05/1635r1
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IEEE C802.16m-09/2761r1
To improve performance of downlink transmission in TDD mode, CL MIMO schemes with beam forming at the
ABS are used. The beam forming matrices at the ABS are calculated from channel measurements in the uplink using sounding reference signals transmitted by AMS. Due to reciprocity of a wireless channel, ABS can translate the measured uplink channel to an estimated downlink channel frequency response, which can be used to calculate downlink beam forming matrices. It should be noted that type of the downlink beam forming usually is not specified, that leaves some freedom for implementation and optimization of the beam forming at the ABS transmitter. However, uncertainty of time-frequency selectivity of the beam forming vector brings some challenges to the design of AMS channel estimation with smoothing.
In this contribution we investigate the impact of time frequency selectivity of the sounding beam forming on the performance of closed loop SU- and MU- MIMO with consideration of channel estimation at the AMS. It has been found that fixing beam forming matrix over PRU doesn’t degrade the performance of the CL MIMO with beam forming, but allows usage of the PRU based channel estimation at the receiver. Further gains in channel estimation can be provided by fixing beam forming over entire subband, so that subband based channel estimation can be utilized. However, it has been found that performance of CL MU-MIMO beamforming can be substantially degraded in some scenarios, so the subband based beam forming is worth for consideration only for CL SU-MIMO case.
Let’s consider SVD beam forming for two correlated channel matrices H
A
and H
B
[1]
H
A



1
0 1
0
 



V
A



1
0 1
0
 

 ,
H
B



1


1



V
B

1


1
1

1
1

 .
2
It can be seen that in spite of relatively high correlation between channel matrices a SVD beam forming matrices
V
A
and V
B
are differ from each other. As a consequence, the frequency correlation of the channel can be broken after SVD beam forming. To demonstrate this effect is also exists in commonly used channel models, a set of
4x2 UMi NLOS channel realizations was generated. For each channel realization a frequency correlation on two adjacent singular vectors was calculated [2]
 k
 v k

1
 
H v k
 
.
The results are shown in Figure 1 for one of the UMi channel realizations where frequency correlation drop has been observed. It can be seen from Figure 1 that correlation for the first singular vector reduces on the subcarrier
#77 (left figure), where the first two singular values has similar values (right figure). The drop of frequency correlation is explained by well known eigenvector subspace swap effect [1].
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IEEE C802.16m-09/2761r1
1.05
1
0.95
0.9
0.85
0.8
10
8
6
4
2
0
-2
-4 0.75
-6
0.7
0 20 40 60 80 100 120
-8
0 50 100 150 200 250 300 350 400 450 500 subc. indx k subc. indx k
Figure 1. Singular vector coherence and singular values of UMi channel model
Drop of the channel correlation on physical adjacent subcarrier is not desired for channel estimation algorithms with smoothing, so to guarantee minimum receiver performance introduction of some constraints on timefrequency selectivity on the beam forming matrices is required. In the next section we investigate the impact of fixing beam forming matrix over certain set of subcarriers with consideration of channel estimation performance at the AMS. Some recommendations are provided.
First, to investigate sensitivity of the performance to frequency selectivity of sounding based beam forming a link level simulation were carried out in UMi test environment. Closed loop MU-MIMO with 3 AMS has been evaluated in 4x2 antenna configurations with half wavelength antenna spacing. The AMS positions have been fixed to -26 0 , 0 and 26 0 . No beam forming feedback delay and perfect channel knowledge for beam forming and
MIMO equalization has been assumed for simulations. Linear MMSE beam forming based on first channel eigenvector was used for MU-MIMO transmission to three AMS
W

1
V (
SNR

V
H
V )

1
, where V

 v
1
, v
2
, v
3

is non-unitary precoding matrix concatenated from the first eigenvector of each AMS channel matrix. CL MU-MIMO was selected for the analysis since it is the most sensitive MIMO to the accuracy of the beam forming vector assignment. So, the results may be considered as an ‘upper’ bound for degradation due to suboptimal beam forming selection on each subcarrier.
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IEEE C802.16m-09/2761r1
10
0
4x2 CL MU-MIMO, 3 MS, SVD-MMSE, 10MHz, UMi NLOS (3kmph), TX/RX sp. = 0.5

10
-1
10
-2
-5
QPSK R = 0.5938, 1 Subc.
QPSK R = 0.5938, 1 PRU
QPSK R = 0.5938, 1 SB
16 QAM R = 0.5208, 1 Subc.
16 QAM R = 0.5208, 1 PRU
16 QAM R = 0.5208, 1 SB
64 QAM R = 0.5694, 1 Subc.
64 QAM R = 0.5694, 1 PRU
64 QAM R = 0.5694, 1 SB
0 5 10 15 20
SNR, dB
Figure 2. MU-MIMO performance for per subcarrier and PRU based beam forming
The packet error rate (PER) versus signal-to-noise ratio obtained by simulations are shown in Figure 2 for three types of beam forming assigment:
 subcarrier based beam forming
 PRU based beam forming
 subband based beam forming
It can be send that using constant beam foming over PRU shows almost the same performance as per subcarrier beam forming at low to medium SNR values (QPSK and 16QAM) and provides loss of about 0.5 dB for high
SNR values (64 QAM) at PER = 10 %. It is expected that the relative difference between per subcarrier and
PRU based beam forming will be further reduced in more practical scenarios with channel measurements errors, calibration imperfections, feedback delays and smaller MU-MIMO rank transmissions. It can be also seen that using subband based beam forming provides substantial performance loss due. In this case usage of subband based beam forming is not well justified for CL MU-MIMO.
A similar analysis has been conducted for SU-MIMO mode. A link level simulation results are shown in Figure
3. It can be seen that SU-MIMO is less sensitive to the frequency selectivity of the beam forming matrices and almost the same performance can be obtained for all three types of beam forming assignment including. For example subband based beam forming is just 0.5 dB worse than per subcarrier or PRU based beam forming at
PER = 10% for any modulation order. In other words further optimization of subband based mean forming assignment is not expected to provide substantial gain in the performance. At the same time usage of constant beam forming matrix for the entire subband may provide additional performance improvement at receiver due to
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usage of subband based channel estimation at the AMS.
4x2 CL SU-MIMO, SVD, 10MHz, UMi NLOS (3kmph), TX/RX sp. = 0.5

10
0
IEEE C802.16m-09/2761r1
10
-1
QPSK R = 0.5588, 1 Subc.
QPSK R = 0.5588, 1 PRU
QPSK R = 0.5588, 1 SB
16QAM R = 0.4902, 1 Subc.
16QAM R = 0.4902, 1 PRU
16QAM R = 0.4902, 1 SB
64QAM R = 0.5359, 1 Subc.
64QAM R = 0.5359, 1 PRU
64QAM R = 0.5359, 1 SB
10
-2
-12 -10 -8 -6 -4 -2
SNR, dB
0 2 4 6 8 10
Figure 3. SU-MIMO performance for subcarrier, PRU and subband based beam forming
To illustrate the gains due to subband based channel estimation over PRU based channel estimation a link level simulations with two dimensional channel estimation algorithm was carried out. In Figure 4 the performance comparison is shown for PRU and subband based channel estimation for subband based beam forming. Pilot pattern for 1 stream with boosting of 2dB has been used. It can be seen that performance improvement of about
0.5 dB can be obtained.
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IEEE C802.16m-09/2761r1
10
0
4x2 CL SU-MIMO, SVD, 10MHz, UMi NLOS (3kmph), TX/RX sp. = 0.5

QPSK, PRU CE
QPSK, SB CE
16QAM, PRU CE
16QAM, SB CE
64QAM, PRU CE
64QAM, SB CE
10
-1
10
-2
-10 -8 -6 -4 -2 0
SNR, dB
2 4 6 8 10
Figure 4. Channel estimation performance in SU-MIMO mode with SVD precoding
-------------------------------------------------- Text Start #1 ------------------------------------------------
{Add the following text on page 489, line 47, section 16.3.7.2.5.7 }
To assist the ABS in determining the precoding matrix to use for SU-MIMO or MU-MIMO, the ABS may request the AMS transmit a sounding signal in an UL sounding channel. The ABS may translate the measured
UL channel response to an estimated DL channel response. The transmitter and receiver hardware of ABS may be calibrated to assist the channel response translation. .
The derived precoding matrix shall be the same for all subcarriers within a PRU.
-------------------------------------------------- Text End #1 ------------------------------------------------
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