Multisector Eigenbeamforming With MMSE Reception in Spatially Correlated Channels

Single-sector eigenbeamforming is effective for obtaining transmit array gain in spatially correlated fading channels while reducing the feedback signaling overhead. However, it may suffer from interference near the sector boundary when applied to the downlink with universal frequency reuse. This interference may not sufficiently be handled by a minimum mean square error (MMSE)-type receiver. To alleviate the interference problem, we consider the use of multisector eigenbeamforming (MEB) in an MMSE receiver, which requires cooperation between adjacent sectors in the same cell. We analyze the performance of the MEB with the use of long-term channel information in terms of the ergodic capacity. Finally, the effectiveness of the proposed MEB near the sector boundary is verified by computer simulation.

[1]  Rohit U. Nabar,et al.  Introduction to Space-Time Wireless Communications , 2003 .

[2]  Mamoru Sawahashi,et al.  Performance Comparison Between Fast Sector Selection and Simultaneous Transmission with Soft-Combining for Intra-Node B Macro Diversity in Downlink OFDM Radio Access , 2006, 2006 IEEE 63rd Vehicular Technology Conference.

[3]  Saman K. Halgamuge,et al.  Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients , 2004, IEEE Transactions on Evolutionary Computation.

[4]  Ranjan K. Mallik,et al.  Bounds and approximations for optimum combining of signals in the presence of multiple cochannel interferers and thermal noise , 2003, IEEE Trans. Commun..

[5]  Mohamed-Slim Alouini,et al.  Outage probability of mimo optimum combining in presence of unbalanced co-channel interferers and noise , 2006, IEEE Transactions on Wireless Communications.

[6]  Jun Tan,et al.  Multicarrier delay diversity modulation for MIMO systems , 2004, IEEE Trans. Wirel. Commun..

[7]  J.H. Winters,et al.  Optimum combining in digital mobile radio with cochannel interference , 1984, IEEE Transactions on Vehicular Technology.

[8]  Preben E. Mogensen,et al.  Baseline E-UTRA Downlink Spectral Efficiency Evaluation , 2006, IEEE Vehicular Technology Conference.

[9]  Armin Dammann,et al.  Analysis of Coded OFDMA in a Downlink Multi-Cell Scenario , 2004 .

[10]  Preben E. Mogensen,et al.  A stochastic MIMO radio channel model with experimental validation , 2002, IEEE J. Sel. Areas Commun..

[11]  Alister G. Burr,et al.  Survey of Channel and Radio Propagation Models for Wireless MIMO Systems , 2007, EURASIP J. Wirel. Commun. Netw..

[12]  Keith Q. T. Zhang,et al.  Outage probability for optimum combining of arbitrarily faded signals in the presence of correlated Rayleigh interferers , 2004, IEEE Transactions on Vehicular Technology.

[13]  Audra E. Kosh,et al.  Linear Algebra and its Applications , 1992 .

[14]  David Tse,et al.  Fundamentals of Wireless Communication , 2005 .

[15]  Hsuan-Ming Feng,et al.  Self-generation RBFNs using evolutional PSO learning , 2006, Neurocomputing.

[16]  Yikang Xiang,et al.  Inter-cell Interference Mitigation through Flexible Resource Reuse in OFDMA based Communication Networks , 2007 .

[17]  Arogyaswami Paulraj,et al.  Performance analysis of linear precoding based on field trials results of MIMO-OFDM system , 2005, IEEE Transactions on Wireless Communications.

[18]  Lajos Hanzo,et al.  Adaptive Minimum Symbol Error Rate Beamforming Assisted Detection for Quadrature Amplitude Modulation , 2008, IEEE Transactions on Wireless Communications.

[19]  Keith G. Balmain,et al.  Multipath performance of adaptive antennas with multiple interferers and correlated fadings , 1999 .

[20]  J. Salo,et al.  An interim channel model for beyond-3G systems: extending the 3GPP spatial channel model (SCM) , 2005, 2005 IEEE 61st Vehicular Technology Conference.