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- 1. Impact of Spatial Correlationtowards the Performance of MIMO Downlink Transmissions Rosdiadee Nordin, Mahamod Ismail Universiti Kebangsaan Malaysia
- 2. LAYOUT• Introduction• Problem Background• Objectives• Methodology• Results & Analysis• Conclusions & Future Work
- 3. INTRODUCTION• MIMO, in combination with OFDMA for IMT-A network, i.e. LTE-A vs. Mobile WiMAX• MIMO as a form of diversity: – Space-Time Coding: achieve maximum antenna diversity & improve wireless link reliability (Alamouti’s) – Spatial Multiplexing: increase data rate, i.e. higher spectral efficiencies (V-BLAST)• OFDMA: allowing efficient and flexible resource allocation
- 4. PROBLEM BACKGROUND• MIMO gain dependent on number of Tx-Rx antenna; 12 RBS=0.0,RMS=0.0 subjected to uncorrelated fading 10 RBS=0.4,RMS=0.4 RBS=0.5,RMS=0.5• Spectral efficiency depends 8 RBS=0.0,RMS=0.9 RBS=0.9,RMS=0.0 capacity (bps/Hz) strongly on the statistical 6 RBS=0.9,RMS=0.9 RBS=1.0,RMS=1.0 behavior of the spatial fading correlation, known as self- 4 interference 2• As the spatial correlation 0 -10 -5 0 5 SNR (dB) 10 15 20 increases, cross-correlation will occur between the spatial **The effect of self-interference needs subchannels to be reduced**
- 5. PROBLEM BACKGROUND • MIMO suffers from self-interference, resulting in ill- conditioned matrices, cause degradation of capacity. • Previous works [5], [6] and [7] suggest the existence of a correlation between antenna elements • Potential capacity gain dependent on the multipath richness – Fully correlated MIMO channel offers only single effective channel, i.e. SISO – Fully de-correlated channel offers multiple capacity benefits[5] D. Gesbert, M. Shafi, D.S Shiu, P.J. Smith, and A. Naguib. “From theory to practice: an overview of MIMO space-time coded wirelesssystems”, Tutorial paper. IEEE Journal on Selected Areas in Communications (JSAC), Vol. 21, No. 3, pp. 281-302, Apr. 2003[6] S. Catreux, P. F. Driessen, and L. J. Greenstein, “Attainable throughput of an interference-limited multiple-input multiple-output (MIMO)cellular system,” IEEE Transactions on Communications, Vol. 49, No. 8, pp. 1307-1311, Aug. 2001.[7] D.-S. Shiu, G. J. Foschini, M. J. Gans, and J. M. Kahn, “Fading correlation and its effect on the capacity of multielement antenna systems,”IEEE Transactions on Selected Areas in Communications, Vol. 48, No. 3, Mar. 2000
- 6. PROBLEM BACKGROUND• Factors contribute towards self-interference: – Multipath angular spread [5] – Separation between Tx and Rx [6] – Antenna element spacing [9] – Array orientation [10][5] D. Gesbert, M. Shafi, D.S Shiu, P.J. Smith, and A. Naguib. “From theory to practice: an overview of MIMOspace-time coded wireless systems”, Tutorial paper. IEEE Journal on Selected Areas in Communications (JSAC),Vol. 21, No. 3, pp. 281-302, Apr. 2003[6] S. Catreux, P. F. Driessen, and L. J. Greenstein, “Attainable throughput of an interference-limited multiple-input multiple-output (MIMO) cellular system,” IEEE Transactions on Communications, Vol. 49, No. 8, pp. 1307-1311, Aug. 2001.[9] M. Chamchoy, S. Promwong, P. Tangtisanon, J. Takada, "Spatial correlation properties of multiantenna UWBsystems for in-home scenarios," IEEE International Symposium on Communications and InformationTechnology, 2004. ISCIT 2004, Vol.2, pp. 1029-1032, Oct. 2004.[10] A. Intarapanich, P. L. Kafle, R. J. Davies, A. B. Sesay, and J. McRory, “Spatial correlation measurements forbroadband MIMO wireless channels,” IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall, Vol.1, pp.52-56, Sept. 2004.
- 7. OBJECTIVES• To investigate the effect of self-interference towards transmission in both MIMO schemes• To compares the performance of both STC and SM schemes in different correlation scenarios by means of subcarrier allocation
- 8. METHODOLOGY (1) Initialization• Allows the user with lowest Set Pk,q=0 for all users, u =1,…, U ; Set Ck,s,q=0 for all users u =1,…, U and spatial subchannels q={1,2,…, Q}; Set s =1 channel gain to have the (2) Main process next best subcarrier gain: While Nq’≠0Nsub fairness vs. error probability { (a) Make a short list according to the users that have less• Involves sorting, comparing power. Find the user u satisfying: Pu,q Pi,q for all i, 1 i u and simple arithmetic. (b) For the user u got in (a), Find sub-carrier n satisfying: | hu,n,q| ≥ | hu,j,q| for all j N• Ranks users from lowest to (c) Update Pu,q’ , Nq and Cu,s,q’ with the s from (b) according to highest channel gain Pu,q= Pu,q+ | hu,n,q|2 Nq= Nq − s Ck,s,q = n s = s +1 (d) Go to the next user in the short list got in (a) until all users are allocated another subcarrier }
- 9. SIMULATION ENVIRONMENT 1 0.9 0.8 0.7 Normalised power 0.6 0.5 0.4 0.3 0.2 0.1 200 300 400 500 600 700 800 900 1000 Excess delay (ns) • Allows separate optimization at both ends • Correlation properties at both Tx/Rx antennas are independent of each other
- 10. RESULTS & ANALYSIS• Robustness of the STBC scheme against the effect of self- interference across all correlation scenarios• Single data stream replicated and Tx over multiple antennas• Redundant data streams are each encoded. Tx signal is orthogonal; reducing self-interference & improving the reliability of the receiver to distinguish between the multiple signals
- 11. RESULTS & ANALYSIS• ML detection in Alamouti’s known to tolerate against moderate level of correlation, which is approximately up to correlation coefficient, RMIMO < 0.8 [15].• However, the implementation complexity of ML receiver needs to be considered – For small MS with low-power requirement – When the delay spread of the channel is large• Complexity of a ML decoder depends on the number of receive antennas and the constellation size of the modulation scheme• For an Nt×Nr MIMO system using M-QAM, the complexity is in the order of MNr.[15] D. Gore, R. W. Heath, and A. Paulraj, “Performance analysis of spatial multiplexing in correlated channels,”IEEE Trans. Commun., 2002.
- 12. RESULTS & ANALYSIS• Difference in SM performance occurs due to the architecture of spatial multiplexing transmission: – probability of the other spatial interferer to transmit the same subcarrier to the desired signal is very high as the spatial subchannel approaches full correlation – MMSE decoder offers a suboptimal solution for equalization - poor ability to reduce effect of interference in the fully correlated channel. – In a highly correlated channel, the presence of self- interference becomes more dominant than the additive noise, thus the symbols’ detection and decoding become a difficult task to the MMSE receiver.
- 13. CONCLUSIONS & FUTURE WORKS• Both STBC and SM suffer from self-interference, degree of impairment increases as degree of spatial correlation increases• Effect of self-interference is highly dominant in SM architecture compared to STBC• Due to the cross paths that occur between the spatial multiplexing of data streams• Future Works: – Minimization of self-interference, focusing on SM scheme based on several allocation strategies – Subcarrier switch-off optimization (green communication)
- 14. 감사합니다!

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