Performance Evaluation of Codebooks Proposed for IEEE 802.16m Amendment IEEE 802.16 Presentation Submission Template (Rev. 9) Document Number: IEEE C80216m-09_0344.

Performance Evaluation of Codebooks Proposed for IEEE 802.16m Amendment

IEEE 802.16 Presentation Submission Template (Rev. 9) Document Number:

IEEE C80216m-09_0344Date Submitted:

2009-01-07Source:

David Mazzarese, Bruno Clerckx, Kwanhee Roh, Wang Zhen, Heewon Kang [email protected] Chul Hwang, Sungwoo Park, Soon-Young Yoon, Hokyu Choi, Jerry PiKaushik Josiam, Sudhir Ramakrishna, Farooq KhanSamsung Electronics

Venue:IEEE 802.16m Session#59, San Diego, US IEEE 802.16m-08/053r1, “Call for Contributions for P802.16m Amendment Text Proposals”. Topic: “DL MIMO and UL MIMO”.

Base Contribution:IEEE C80216m-09_0344

Purpose:Discussion and approval

Notice:This document does not represent the agreed views of the IEEE 802.16 Working Group or any of its subgroups. It represents only the views of the participants listed in the “Source(s)” field above. It is offered as a basis for discussion. It is not binding on the contributor(s), who reserve(s) the right to add, amend or withdraw material contained herein.

Release:The contributor grants a free, irrevocable license to the IEEE to incorporate material contained in this contribution, and any modifications thereof, in the creation of an IEEE Standards publication; to copyright in the IEEE’s name any IEEE Standards publication even though it may include portions of this contribution; and at the IEEE’s sole discretion to permit others to reproduce in whole or in part the resulting IEEE Standards publication. The contributor also acknowledges and accepts that

this contribution may be made public by IEEE 802.16.

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Introduction

• Several codebooks have been proposed in the base contribution C80216m-09_0279.

• This contribution provides supporting simulations and analysis of base codebooks.

Codebook-based feedback

• Codebooks are used in uplink feedback to the BS for supporting downlink precoding

• 3 codebook-based feedback modes in SDD– Standard: base codebook– Adaptive: correlation matrix transformation– Differential: differential PMI feedback

Base Codebook Analysis

Base Codebook CandidatesReference Author Label used in figures

806.16e 802.16e 16e_3bit

806.16e 802.16e 16e_6bit

C80216m-09_0279 David Mazzarese 09/0279_4bit

C80216m-09_0279 David Mazzarese 09/0279_6bit

C80216m-09_0056 Guangjie Li 09/0056_4bit

C80216m-09_0056 Guangjie Li 09/0056_6bit

C80216m-09_106r1 Yang Tang 09/0106_6bit

C802.16m-08_983

C80216m-MIMO-08/69

Jaewan Kim 08/983_4bit

C80216m-08_1101

C80216m-MIMO-08/74

Bishwarup Mondal 08/1101_4bit

C80216m-MIMO-08_067 Shaohua li 08/067_6bit

C80216m-08/916

C80216m-08/1264r1

Ron Porat 08/916_4bit

Measures of Codebook GoodnessMeasure Description

Throughput First and foremost measure

Feedback overhead Codebook size (number of bits)

DFT structure Best for calibrated correlated linear arrays

Block-diagonal matrices Adapted for dual polarized arrays at BS

Full nested property Ranks 2, 3 and 4 matrices are composed of rank 1 precoders: CQI computation complexity reduction

Constant modulus matrix elements

Good for power amplifier transmit power balance, good for PAPR in precoded systems

QPSK alphabet CQI computation complexity reduction by avoiding numerous complex multiplications

Avoidance of rank deficiency weakness

Any combination of 2 to Nt rank 1 precoders produces an invertible matrix: desirable for simple implementation complexity of ZFBF

Comparison of 4Tx Codebooks

09/0279 09/0279 802.16e 09/0056 09/0056 09/0106 08/983 08/1101

Feedback overhead

4 bits 6 bits 3/6 bits 4 bits 6 bits 6 bits 4 bits 4 bits

Performance (SLS)

C: good

U: good

C: good

U: good

C: bad

U: good

C: good

U: good

C: good

U: good

C: good

U: good

C: good

U: bad

C: bad

U: bad

DFT structure Yes Yes No Yes Yes Yes Pure Yes

Block-diagonal matrices

No No No No No Yes No No

Full nested property

Full Full No No No Yes (rank 1 and 2)

Yes No

Constant modulus

Yes No No No No No Yes Yes

QPSK alphabet No No No No No No No Yes

Avoidance of rank deficiency

Yes Yes Yes Yes No No Yes No

C: correlated channelsU: uncorrelated channels

Performance Evaluation

Simulation Environments

• SU MIMO SLS in DL 4x2– ULA: uncorrelated, correlated channels

• MU MIMO (ZFBF) SLS in DL 4x2– ULA: uncorrelated, correlated channels

SU MIMO SLS in DL 4x2Uncorrelated Channel (4 lambdas)

SU CL MIMO SLS (uncorrelated channel)

91.00

98.26

97.00

100.00

98.18

99.84

99.76

92.27

95.19

80.00 85.00 90.00 95.00 100.00 105.00

16e_3bit

16e_6bit

09/0056_4bit

09/0056_6bit

09/0279_4bit

09/0279_6bit

09/0106_6bit

16e_3bit Transformed

16e_6bit Transformed

Sector Throughput relative to the best codebook

SU MIMO SLS in DL 4x2Correlated Channel (1/2 lambda)

SU CL MIMO SLS (correlated channel)

88.91

94.78

98.68

99.49

98.75

99.71

100.00

100.37

100.37

80.00 85.00 90.00 95.00 100.00 105.00

16e_3bit

16e_6bit

09/0056_4bit

09/0056_6bit

09/0279_4bit

09/0279_6bit

09/0106_6bit

16e_3bit Transformed

16e_6bit Transformed

Sector Throughput relative to the best codebook

SU MIMO SLS in DL 4x2• 16e codebooks lose 6% and 11% throughput in correlated channels in

reference to the best 6-bit codebook• DFT-based codebooks are robust in all scenarios• 6-bit DFT-based codebooks are as good or better than 16e in

uncorrelated channels• All 6-bit DFT-based codebooks are within 0.5% of each other• All 4-bit DFT-based codebooks are within 1% of each other• The 4-bit DFT-based codebooks lose only 1% and 3% to the 6-bit DFT-

based codebooks in correlated and uncorrelated channels, respectively• The transformation brings the performance of small codebooks to the

same level as the 6-bit DFT-based codebooks in correlated channels• The transformation is ineffective in uncorrelated channels

SU MIMO SLS in DL 4x2

4-bit codebook seems like a reasonable choice, since it requires lower computational complexity and feedback overhead than a 6-bit codebook

MU MIMO SLS in DL 4x2Uncorrelated Channel (10 lambdas)

MU MIMO (uncorrelated channel)

99.15

93.26

100.00

93.93

99.81

99.05

100.57

94.31

100.66

94.88

100.76

99.81

70.00 75.00 80.00 85.00 90.00 95.00 100.00 105.00

16e_6bit

09/0056_4bit

09/0056_6bit

09/0279_4bit

09/0279_6bit

09/0106_6bit

16e_6bit Transformed

09/0056_4bit Transformed

09/0056_4bit Transformed

09/0279_4bit Transformed

09/0279_6bit Transformed

09/0106_6bit Transformed

Sector throughput relative to the best codebook without transformation

MU MIMO SLS in DL 4x2Correlated Channel (1/2 lambda)

MU MIMO (correlated channel)

78.47

91.87

96.54

92.78

100.00

99.76

105.82

103.27

105.64

102.85

105.64

105.34

70.00 75.00 80.00 85.00 90.00 95.00 100.00 105.00 110.00

16e_6bit

09/0056_4bit

09/0056_6bit

09/0279_4bit

09/0279_6bit

09/0106_6bit

16e_6bit Transformed

09/0056_4bit Transformed

09/0056_4bit Transformed

09/0279_4bit Transformed

09/0279_6bit Transformed

09/0106_6bit Transformed

Sector throughput relative to the best codebook without transformation

MU MIMO SLS in DL 4x2

• 16e codebooks lose 1% and 22% throughput in correlated channels in reference to the best 6-bit codebook

• DFT-based codebooks are robust in all scenarios• 6-bit DFT-based codebooks are as good or better than 16e in uncorrelated

channels• All 6-bit DFT-based codebooks are within 1% of each other in uncorrelated

channels• All 6-bit DFT-based codebooks are within 1% of each other in correlated

channels, except 09/0056_6bit which loses 4.5% to 09/0279_6bit• All 4-bit DFT-based codebooks are within 1% of each other• The 4-bit DFT-based codebooks lose only 7% and 8% to the 6-bit DFT-based

codebooks in correlated and uncorrelated channels, respectively• The transformation allows the performance of 4-bit codebooks to exceed the 6-

bit DFT-based codebooks by 3% in correlated channels• The transformation is ineffective in uncorrelated channels

MU MIMO SLS in DL 4x2

The average sector throughput with MU MIMO in correlated channels is about 1.5 times higher than in uncorrelated channels.

This fact stresses the importance of 1. Optimizing the codebook in the correlated channel2. Calibrating the antenna array at the BS

• to avoid random phase effects• to benefit from the DFT-based structure

Thus a 4-bit codebook seems like a reasonable choice, since it requires lower computational complexity and feedback overhead than a 6-bit codebook

Feedback Overhead

• Penalty of 6-bit codebook vs. 4-bit codebook– It depends on feedback channel design

• CQICH or feedback header used for PMI feedback?• How many PMIs carried in one CQICH?• Subband info carried in same CQICH as PMI?• How many best subbands?

– It also depends on the number of users that feedback PMI

• More knowledge of feedback channel design and analysis of feedback procedure is necessary before finally choosing between a 4-bit and a 6-bit base codebook

AppendixSimulation Assumptions

Number of Antennas2 transmitter, 2 receiver [2Tx, 2Rx]4 transmitter, 2 receiver [4Tx, 2Rx]4 transmitter, 4 receiver [4Tx, 4Rx]

Antenna configurationULA: 0.5 lambda; 4 lambda, 10 lambdaSplit Linear Array, Dual Polarized Array

MIMO Scheme

1. Closed-loop single user with dynamic rank adaptation2. Zero-forcing multiple user MIMOSchedule from 1 to 2 users dynamically based on the same rank-1 PMI feedback. No SU/MU

mode adaptation.

Channel Model Modified Ped-B 3km/h

Channel correlation Scenario1. Uncorrelated Channel : 4 lambda antenna spacing, angular spread of 15 degrees 2. High correlated channel: 0.5 lambda antenna spacing, angular spread of 3 degree

PAPR 1. No constraint on per-antenna power imbalance 2. Limitation of per-antenna power imbalance by scaling in every subframe

Antenna Calibration 1. Ideal antenna calibration (mandatory)2. Uncalibrated antennas (optional) Random phase on each transmit antenna + Random delay between each pair of adjacent

transmit antennas (uniformly distributed between 0 and N samples) Fixed for one drop

OFDM parameters 10 MHz (1024 subcarriers)

OFDM symbols per subframe 6

Permutation Localized

Number of total RU in one subframe 48

Scheduling Unit

Whole band (48 PRUs)12 subbands

1 subband = 4 consecutive PRUs1 PMI and 1 CQI feedback per subband

Number of RUfor PMI and CQI calculation

4 which is same as in IEEE 802.16e

CQI, PMI feedback period Every 1 frame (5ms)

Feedback delay 1 frame (5ms)

Link Adaptation(PHY abstraction)

QPSK 1/2 with repetition 1/2/4/6, QPSK 3/4, 16QAM 1/2, 16QAM 3/4, 64QAM 1/2, 64QAM 2/3, 64QAM 3/4, 64QAM 5/6

m

dB

AA ,12min2

3

dB3

HARQ

Chase combining, non-adaptive, asynchronous. HARQ with maximum 4 retransmissions, 4 subframes ACK/NACK delay, no error on ACK/NACK.HARQ retransmission occurs no earlier than the eighth subframe after the

previous transmission.

Scheduling No control overhead, 12 subbands of 4 PRUs each, latency timescale 1.5s

MIMO receiver Linear Minimum Mean Squared Error (LMMSE)

Data Channel Estimation Perfect data channel estimation

Feedback Channel Measurement Perfect feedback channel measurement

Cellular LayoutHexagonal grid, 19 cell sites, wrap-around,

3 sectors per site

Distance-dependent path loss L=130.19 + 37.6log10(.R), R in kilometers

Inter site distance 1.5km

Shadowing standard deviation 8 dB

Antenna pattern (horizontal)(For 3-sector cell sites with fixed

antenna patterns) = 70 degrees, Am = 20 dB

Users per sector 10 (EMD)

Scheduling Criterion Proportional Fair (PF for all the scheduled users)

Feedback channel error rate No error

23/#NN

Power fluctuation among antennas• Constant modulus property

– Definition: Every elements of codebook vector has same magnitude– Good for per-antenna peak power limit– DFT-based codebooks have a constant modulus property, while 16e-based do not

Power [watt]

5

Ant-1 Ant-2 Ant-3 Ant-4 Ant-1 Ant-2 Ant-3 Ant-4

5

Power [watt]

Total power limitation

Per-ant. Peak power limitation

Sum power is limited to 20W

Per-ant power limited to 5W

Power adjustment subframe by subframe