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Joint Coding and Modulation Diversity for ac

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1 Joint Coding and Modulation Diversity for 802.11ac
January 2010 doc.: IEEE /0084r3 Joint Coding and Modulation Diversity for ac Date: Authors: Brian Hart, Cisco Systems

2 Abstract In ad system, according to the IEEE /0433r2 document, the rotation modulation technique has already been adopted in QPSK modulation. Based on our recent research, this technique can also improve the overall performance of ac system, especially in MIMO-OFDM scenario. Therefore, we recommend to introduce this technique to ac system.

3 Transmitter/Receiver Block Diagram
NOTES — Red block is our proposed amendment. —There may be 1 or 2 FEC encoders when BCC encoding is used. —When LDPC encoding is used, the interleavers are not used.

4 Amendment and simulation are based on the document IEEE 802
Amendment and simulation are based on the document IEEE n-2009 and IEEE /0992r18. In the amendment, we use rotational modulation method to combine with time diversity of channel coding, spatial diversity of MIMO and frequency diversity of OFDM, which is named joint coding and modulation diversity (JCMD) . As compared with JCMD, the processing scheme in IEEE n Standard is named bit interleaved coded modulation (BICM) for simplicity.

5 Basic principle of the rotational modulation
According to rotational matrix,rotate the conventional modulated symbol. The relationship between conventional modulated complex symbol A + j*B and the rotational modulated complex symbol X + j*Y is shown in equation: where A and B are the I (in-phase) and Q (quadrature) component of the normal QAM, respectively; X and Y are the I and Q component of rotated QAM, respectively

6 Our Proposed Rotation Matrix to 802.11ac system
Modulation Proposed Rotation Matrix QPSK 16QAM 64QAM 256QAM

7 Basic principle of the Spatial Interleaving
In this process , denotes rotated symbol on the stream at time sample. So the interleaving is usual spiral layer interleaving process among all streams at the same time. The method is as follow: Where is the number of spatial streams. For example, consider the case, =4: Corresponding, uses the inverse algorithm at the receiver as follow:

8 Basic principle of the Spatial Q-Interleaving
In the spatial Q-interleaving process, I components of the complex signals are unchanged, while Q components of signals are changed as follows: That is to say, Q component on stream i will be moved to the stream (Nss-i-1). Corresponding, use the inverse algorithm at the receiver, which is the same as above spatial Q-Interleaving equation

9 Basic principle of the Frequency domain Q-interleaveing
In the frequency domain Q-interleaving process, the I components of the complex signals are unchanged, while Q components of signals are changed as follows: is the number of subcarriers for data. That is to say, Q component on subcarrier i will be moved to the subcarrier (Nss-i-1). Corresponding, uses the inverse algorithm at the receiver, which is the same as above frequency Q-interleaving equation.

10 Basic principle of Beamforming
According to the theory of SVD,the channel matrix H can be decomposed as where D is a non-negative diagonal matrix of Pre-coding: For example, we assume

11 Basic principle of Pre-decoding
The received signal vector is modeled as shown in Equation SVD-decoding: So For each stream,

12 Basic principle of demodulation
Due to spatial Q-interleaving and frequency Q-interleaving, fading coefficient of I component is usually different from that of Q component

13 Basic principle of demodulation
For example, consider the R-QPSK(rotational quadrature phase-shift keying): The procedure for demodulation is shown as follows: Compute the distance between the received point and each reference constellation point. The relationship between the reference constellation point and the rotational constellation point is shown as follows: so

14 Basic principle of demodulation
2) Compute the Likelihood ratio (LLR) for every bit. The LLR is the input of the decoder. For the first bit : For the second bit: There is also a simplified algorithm to compute the LLRs: Similarly, for M-ary QAM(Quadrature amplitude modulation), we should compute LLRs for bits.

15 Simulation Parameters
Values PHY scheme OFDM Antenna scheme 2*2 ,4*4,8*8 Length of FFT 64 Number of subcarriers 56 Number of data subcarriers 52 Code Type LDPC, BCC Code Rate 3/4,5/6 Modulation Type QPSK 16QAM 64QAM 256QAM Channel Type TGac Channel Model E LOS,NLOS[4,5] Coherent Bandwidth Coherent Time 1/0.4326=2.427s Bandwidth 20MHZ Sub-carrier spacing 312.5kHZ Channel estimation Ideal channel estimation, LS channel estimation (consider the phase noise)

16 MCS (modulation and coding scheme) (2*2)
CODE RATE Number of OFDM symbols per frame Block Size 2 QPSK 3/4 6 1248 4 16-QAM 1668 7 64-QAM 5/6 8 256-QAM 1664

17 Rotation Modulation LOS (2*2),LDPC
MCS GAIN (dB) (FER=0.01) 2 7.2 4 4.8 7 4.5 8 1.8

18 Rotation Modulation LOS (2*2), BCC
MCS GAIN (dB) (FER=0.01) 2 7.4 4 5.6 7 5.2 8 2.3

19 Rotation Modulation LOS (2*2),LDPC vs BCC
Gain(dB) (FER=0.01) BICM-LDPC vs BICM-BCC 0.72 JCMD-BCC 6.72 LDPC-coded BICM with much higher complexity only obtains 0.72 dB SNR gain as compared with BCC-coded BICM. BCC-coded JCMD with much lower complexity obtains significant 6.72 dB SNR gain as compared with LDPC-coded BICM.

20 Rotation Modulation NLOS(2*2) ,LDPC
MCS GAIN (dB) (FER=0.01) 2 7.2 4 4.7 7 4.6 8 1.9

21 Rotation Modulation NLOS(2*2) , BCC
MCS GAIN (dB) (FER=0.01) 2 7.2 4 5.4 7 5.1 8 2.2

22 Rotation Modulation NLOS (2*2),LDPC vs BCC
Gain(dB) (FER=0.01) BICM-LDPC vs BICM-BCC 0.48 JCMD-BCC 6.76 LDPC-coded BICM with much higher complexity only obtains 0.48 dB SNR gain as compared with BCC-coded BICM. BCC-coded JCMD with much lower complexity obtains significant 6.76 dB SNR gain as compared with LDPC-coded BICM.

23 Rotation Modulation NLOS(4*4) ,LDPC
MCS Number of OFDM symbols per frame Block Size GAIN (dB) (FER=0.01) 2 6 1248 7.2 4 1668 4.24

24 Rotation Modulation NLOS(8*8) ,LDPC
MCS Number of OFDM symbols per frame Block Size GAIN (dB) (FER=0.01) 2 6 624 7.25 4 1248 4.25 2.13

25 Effect of phase noise The phase noise will be specified with a pole-zero model. PSD(0) = -100 dBc/Hz pole frequency fp = 250 kHz zero frequency fz = kHz This model results in PSD(infinity) = -130 dBc/Hz,

26 Effect of phase noise

27 Effect of phase noise MCS MODULATION CODERATE Block Size IDEAL H LS
LS+PN 2 QPSK 3/4 1248 7.0 6.6 4 16-QAM 1668 4.5 4.0 6 64-QAM 2.8 2.7 2.6

28 Effect of Amplitude distortion
The PAPR (Peak to Average Power Ratio) and Cubic Metric of JCMD are almost the same as that of BICM, so amplitude distortion does not change the relative gain.

29 Hardware Platform The platform Rohde&Schwarz AMU (fading simulator)
2*FSV(signal analyzer) 2*SMBV(vector signal generator) PicoChip PC203 Baseband Unit

30 Hardware Simulation Results
SISO: JCMD obtains 2 .1dB SNR gain at FER=0.01 as compared with BICM.

31 June 2010 doc.: IEEE /xxxxr0 Conclusions The proposed JCMD can achieve obvious SNR gain (up to 7.25dB) over the current ac schemes in all the secenarios (including LOS and NLOS channels, BCC and LDPC). Even the JCMD using BCC can obtain significant SNR gain (up to 6.7dB) over the current ac schemes using LDPC. For 2*2 ,4 * 4 and 8 * 8 antenna schemes, JCMD can keep the similar SNR gains. The phase and amplitude distortions do not change the relative gains. In a word, JCMD is simple, efficient, robust and energy-saving, thus is suitable for ac to realize“Green Communication”. Brian Hart, Cisco Systems

32 Strawpoll Do you accept JCMD as an optional enhanced coded modulation scheme for ac ? -Yes -No -Abstain

33 References IEEE P Wireless LANs PHY/MAC Complete Proposal Specification, Erceg, V. et al. “TGn Channel Models.” Doc. IEEE /940r4. Breit, G. et al., “TGac Channel Model Addendum,” Doc. IEEE /0308r12 IEEE n-2009 IEEE /0992r18


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