Cooperative multi-user MIMO based on limited feedback in downlink OFDM systems

Multi-cellular radio systems are often limited due to the presence of cochannel interference. Physical layer concepts as e.g. interference rejection combining, optimize the receiver side and thus strengthen the signal while combating the interference at the terminal side only. It is well known that joint transceiver optimization, i.e. coordinated joint transmission from several base stations, yields large capacity improvement for downlink transmission. However, the performance highly depends on the available channel knowledge. We focus on how to realize a decentralized and limited cooperative downlink transmission in a multi-cellular network. This yields the crucial question: Is an efficient cooperative transmission possible by using simple channel quality identifiers, or is channel state information at the transmitter mandatory? Further, we use minimum mean square error equalization at the terminal side to combat residual cochannel interference. For baseline we apply receiver optimization only and compare these results with those obtained from cooperative transmission. We demonstrate potential capacity gains in a cellular orthogonal frequency division multiplexing system and their scaling with the number of cooperating antenna arrays.

[1]  Robert W. Heath,et al.  Switching between diversity and multiplexing in MIMO systems , 2005, IEEE Transactions on Communications.

[2]  L. Thiele,et al.  Capacity Scaling of Multi-User MIMO with Limited Feedback in a Multi-Cell Environment , 2007, 2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers.

[3]  Naresh Sharma,et al.  Increasing the peak data rate of 3G downlink packet data systems using multiple antennas , 2003, The 57th IEEE Semiannual Vehicular Technology Conference, 2003. VTC 2003-Spring..

[4]  Shlomo Shamai,et al.  On the achievable throughput of a multiantenna Gaussian broadcast channel , 2003, IEEE Transactions on Information Theory.

[5]  Federico Boccardi,et al.  A Near-Optimum Technique using Linear Precoding for the MIMO Broadcast Channel , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[6]  Jack M. Winters,et al.  Optimum Combining in Digital Mobile Radio with Cochannel Interference , 1984, IEEE Journal on Selected Areas in Communications.

[7]  Lars Thiele,et al.  Multi-Cell Channel Estimation using Virtual Pilots , 2008, VTC Spring 2008 - IEEE Vehicular Technology Conference.

[8]  L. Thiele,et al.  On the value of synchronous downlink MIMO-OFDMA systems with linear equalizers , 2008, 2008 IEEE International Symposium on Wireless Communication Systems.

[9]  Angel E. Lozano,et al.  Approaching the MIMO Capacity with a Low-Rate Feedback Channel in V-BLAST , 2004, EURASIP J. Adv. Signal Process..

[10]  Thomas Bonald A Score-Based Opportunistic Scheduler for Fading Radio Channels , 2004 .

[11]  L. Thiele,et al.  A Fair Score-Based Scheduler for Spatial Transmission Mode Selection , 2007, 2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers.

[12]  Robert W. Heath,et al.  Shifting the MIMO Paradigm , 2007, IEEE Signal Processing Magazine.

[13]  V. Jungnickel,et al.  Synchronization of cooperative base stations , 2008, 2008 IEEE International Symposium on Wireless Communication Systems.

[14]  Lizhong Zheng,et al.  Diversity and multiplexing: a fundamental tradeoff in multiple-antenna channels , 2003, IEEE Trans. Inf. Theory.