Orthogonal Linear Beamforming in MIMO Broadcast Channels

The problem of joint linear beamforming and scheduling in a MIMO broadcast channel is considered. We show how orthogonal linear beamforming (OLBF) can be efficiently combined with a low-complexity user selection algorithm to achieve a large portion of the multiuser capacity. The use of orthogonal transmission enables the transmitter to calculate exact signal-to-interference plus noise ratio (SINR) values during the user selection process. The knowledge of multiuser interference proves to be of particular importance for user scheduling as both the number of users in the cell and the average signal-to-noise ratio (SNR) decrease. The sum capacity of our scheme is characterized in the low-SNR regime, providing analytical results on the performance gain over zero-forcing beamforming (ZFBF). Numerical results show gains over both suboptimal and optimal ZFBF techniques in different scenarios.

[1]  Babak Hassibi,et al.  A Comparison of Time-Sharing, DPC, and Beamforming for MIMO Broadcast Channels With Many Users , 2007, IEEE Transactions on Communications.

[2]  David Gesbert,et al.  Efficient Metrics for Scheduling in MIMO Broadcast Channels with Limited Feedback , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[3]  Emre Telatar,et al.  Capacity of Multi-antenna Gaussian Channels , 1999, Eur. Trans. Telecommun..

[4]  Nihar Jindal Finite Rate Feedback MIMO Broadcast Channels , 2006 .

[5]  Shlomo Shamai,et al.  The capacity region of the Gaussian MIMO broadcast channel , 2004, International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings..

[6]  Sergio Verdú,et al.  Spectral efficiency in the wideband regime , 2002, IEEE Trans. Inf. Theory.

[7]  Rick S. Blum,et al.  Multiuser diversity for a dirty paper approach , 2003, IEEE Communications Letters.

[8]  Andrea J. Goldsmith,et al.  Finite-Rate Feedback MIMO Broadcast Channels with a Large Number of Users , 2006, 2006 IEEE International Symposium on Information Theory.

[9]  M. J. Gans,et al.  On Limits of Wireless Communications in a Fading Environment when Using Multiple Antennas , 1998, Wirel. Pers. Commun..

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

[11]  Nihar Jindal MIMO broadcast channels with finite rate feedback , 2005, GLOBECOM.

[12]  N.D. Sidiropoulos,et al.  On downlink beamforming with greedy user selection: performance analysis and a simple new algorithm , 2005, IEEE Transactions on Signal Processing.

[13]  Babak Hassibi,et al.  On the capacity of MIMO broadcast channel with partial side information , 2003, The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003.

[14]  Harish Viswanathan,et al.  Downlink capacity evaluation of cellular networks with known-interference cancellation , 2003, IEEE J. Sel. Areas Commun..

[15]  Babak Hassibi,et al.  On the capacity of MIMO broadcast channels with partial side information , 2005, IEEE Transactions on Information Theory.

[16]  D. Gesbert,et al.  Low Complexity Scheduling and Beamforming for Multiuser MIMO Systems , 2006, 2006 IEEE 7th Workshop on Signal Processing Advances in Wireless Communications.

[17]  Andrea J. Goldsmith,et al.  On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming , 2006, IEEE Journal on Selected Areas in Communications.