Dynamic subcarrier allocation with ESINR metric in correlated SM-OFDMA
Dynamic Subcarrier Allocation with ESINR Metric in Correlated SM-OFDMA Wireless Advanced 2010 Rosdiadee Nordin, Prof. Joe McGeehan & Dr. Simon University of Bristol Centre for Communications Research
Presentation Outline Self-interference DSA-ESINR Simulation Parameters Results & Analysis Conclusion Centre for Communications Research
3 Correlation in MIMO Correlation occurs due to: antenna location/spacing lack of scatterers angular spread. Resulting in self-interference. Retransmissions and equalisation do notimprove the BER performance.
4 Self-Interference MIMO only works when the channel is inlow correlation. In practice: h’ s0 h’ r0 r0=r1=h’(s0+s1) BS h’ MS Scenario: all spatial layers ` h’ are fully correlated s1 r1 Mathematically: If h’ coefficients are correlated, then [H] is [S] =[H]-1[R] ill-conditioned matrix and difficult to invert
5 ESINR Metric Is the performance metric to determine thesubcarrier allocation. MMSE filter q= spatial layer Main spatial layer Gk H k qq 2 Es q N ESINR k Gk H k qj, j q 2 2 2 E s Gk qq Gk qj, j q Knowledge of self-interference k= subcarrier index
6 DSA-ESINR Involves sorting, comparing and simplearithmetic. Ranks users from lowest to highest ESINR. Fairness: Allow poor users to have the next‘best’ subcarriers. Prevents users from sharing the samesubcarrier with the adjacent layer (interferer).
7 System Model X1 Tx1 Rx1 H1 X1 With Index 1 Transmitter at Base Station OFDM H3 X1User k Input With Index 2 Data Scrambling/ FEC/ Symbol Serial to Parallel& DSA H2 Rx2 X1X2 Puncturing/ Interleaving Mapping Spatial Multiplexing mapping X2 Tx2 With Index 3 H4 X2 X2 OFDM With Index 4 Uplink process Index 1 2 3 4 Downlink process Index 4 ESINR and channel Index 1 DSA Index 2 } DSA-ESINR gain feedback from other users Scheme Index 3 Index 2 Index 3 Index 1 Index 4 } DSA-Scheme 1 ESINR1 ESINR2 [ H3 ] [ H4 ] ESINR calculation Receiver at Mobile Station k [ H1 H3 ] [ H2 H4 ] S1 Y1 DSA OFDM User k Deinterleaving/ S1 S2 Parallel to MMSE [ H1 H3 ] Demapping Symbol Output Depuncturing/ Viterbi Serial& De- Linear Demapping Data Decoding/ Descrambling Multiplexing Detection Y2 DSA S2 [ H2 H4 ] Demapping OFDM
8 Compared against… Maximum Gain Sort-Swap (MGSS): Sort subcarriers pairs by metric of total perceived gain. Swap subcarriers between users. Two parts: initial allocation and iteration. ESINR metric is used to improve theallocation process.
9 Simulation Setup Simulated under BPSK, ½ rate based on V-BLAST (2×2). Nsub= 768, NFFT= 1024 for 16 users, 48subcarriers per user. 1 0.93GPP-SCM ‘Urban Micro’: 0.8 0.7• RMS delay spread= 251 ns Normalised power 0.6• Excess delay= 1200 ns 0.5 0.4• 2000 i.i.d Rayleigh 0.3 0.2 0.1 200 300 400 500 600 700 800 900 1000 Excess delay (ns)
17 Pdf distribution across SNR 1.8 2 SNR= 10 dB SNR= 10 dB 1.6 SNR= 20 dB 1.8 SNR= 20 dB SNR= 30 dB SNR= 30 dB 1.4 1.6p(correlation coefficient) 1.4 p(correlation coefficient) 1.2 1.2 1 1 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 0 0 -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 correlation coefficient correlation coefficient DSA-ESINR MGSS-ESINR
18 Conclusions ESINR with a combination of DSA can minimise the effect of self-interference. Outperforms other forms of suboptimal allocation by 3 dB at BER=10-3 and known as MGSS . Allocation improves as SNR increase.