1. Feedback for long term beamforming
Document Number: C802.16m-09/1427r1
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Source: Intel Corporation, Yuan Zhu
Qinghua Li
Alexi
Eddie Lin
Huaning Niu
Guangjie Li
Yang-seok Choi
Hujun Yin )
Doron Ayelet
Re: Category: AWD comments / Area: Chapter “Comments on AWD UL-CTRL” m amendment working document
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2. Outlines Introduction Covariance matrix feedback vs. PMI feedback
SLS results
Conclusions
Proposed text

3. Long term beamforming Long term beamforming Application scenario
A single beamforming matrix is applied to whole band over long period.
Applying same beamforming matrix over long period is already in e.
Application scenario
Highly correlated antenna
Low mobility
Feedback quantities
Quantized covariance matrix
Precoding matrix index (PMI)
Compute PMI from covariance matrix
Compute PMI from channel matrix estimated from midamble

4. Quantization error reduction
Quantization error of PMI is reduced as codebook resolution. 6-bit codebook has smaller error than 4-bit one.
Hierarchical codebook of 10-bit resolution can be formed by concatenating 6-bit base codebook and 4-bit differential codebook.
Hierarchical codebook is used in same way as base codebook.
The complexity of searching hierarchical codebook can be reduced by hierarchical search from base code book to differential code book.

5. Quantization of beaming direction
Compute ideal beamforming matrix and then quantize it.

6. Covariance matrix vs. PMI
Method I
Method II
Feedback infomation
Quantized channel covariance matrix over PMI or MAC message.
PMI over FBCH
Number of feedback bits
28 bits for 4-Tx antennas, 120 bits for 8-Tx antennas
4-Tx: 6+4 = 10 bits
8-Tx: = 12 bits
Operations
MS: measure covariance matrix, quantize principal eigenvector (for CQI estimation).
MS: measure covariance matrix, search codebook.

7. SLS performances, SU-MIMO, AS=15º, PMI feedback Period=8Frames
Method I (28 bits)
Method II (6 bits)
Method II (10 bits)
Calibrated antenna array
100%
99.8%
100.3%
Uncalibrated antenna array
95.3%
98%
Uncalibrated, BS 45o cross-pole antennas
96.5%
98.7%
Uncalibrated, BS cross-pole, MS V/H cross-pole
99%

8. SLS performances, SU-MIMO, AS=3º, PMI feedback Period=8Frames, PUSC 30km/h
Method I (28 bits)
Method II (6 bits)
Method II (10 bits)
Calibrated antenna array
100%
99.3%
100.7%
Uncalibrated antenna array
93.5%
96.1%
Uncalibrated, BS 45o cross-pole antennas
96.4%
98.1%
Uncalibrated, BS cross-pole, MS V/H cross-pole
98.4%
99.9%

9. LLS performance for MU-MIMO

10. Conclusions
Feeding back PMI and Feeding back covariance matrix have almost exactly same performance.
Feed back PMI reduces overhead by 3x as compared to feeding back covariance matrix for 4-Tx BS antennas.
PMI feedback should be adopted for long term beamforming.

12. Appendix

13. General SLS parameters
Parameter Names
Parameter Values
Network Topology
57 sectors wrap around, 10 MS/sector
MS Channel
ITU PB3km/h or VA30km/h
Frame Structure
TDD, 5DL, 3 UL
Feedback Delay
5ms
Inter cell Interference Modeling
Real
Antenna Configuration
4Tx, 2 Rx, BS antenna spacing 0.5λ
Codebook configuration
16m (4,1,6), 16m D(4,1,4)
Tx Channel Covariance Matrix
28 bits quantized
Long term feedback period
8 frames
PMI error
free
PMI calculation
Maximize V’RV
System bandwidth
10MHz, 864 data subcarriers
Permutation type
AMC, 48 LRU or PUSC
CQI feedback
1Subband=4 LRU, ideal feedback

14. Covariance matrix quantization method, AWD
Diagonal element: 1 bit for amp {0.6, 0.9}
Down triangle elements: 1 bit for amp {0.1, 0.5}, 3 bits for phase {0,π/8,π/4, 3π/8, π /2, 5π/8, 3 π /4, 7π /8}

15. Covariance matrix vs. measure channel
Long term PMI can be computed from measured covariance matrix or channels estimated from midambles.
Using covariance matrix delivers better performance for uncalibrated, cross-pole antennas.