IEEE Transactions on Communications
Linear processing and sum throughput in the multiuser MIMO downlink?
IEEE Transactions on Wireless Communications
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 4
A joint source and relay power allocation scheme for a class of MIMO relay systems
IEEE Transactions on Signal Processing
Investigation into SVD based beamforming over Rician MIMO channels
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Utility of beamforming strategies for secrecy in multiuser MIMO wiretap channels
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Linear precoding for multiuser MIMO systems with multiple base stations
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Sarnoff'10 Proceedings of the 33rd IEEE conference on Sarnoff
Coordinated zero-forcing beamforming in multipoint MIMO networks for backhaul applications
MILCOM'09 Proceedings of the 28th IEEE conference on Military communications
Optimum MMSE transceiver designs for the downlink of multicell MIMO systems
MILCOM'09 Proceedings of the 28th IEEE conference on Military communications
Efficient weighted sum rate maximization with linear precoding
IEEE Transactions on Signal Processing
Linear transmission for rate optimization in MIMO broadcast channels
IEEE Transactions on Wireless Communications
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We consider a single-cell multiple-input multiple-output (MIMO) downlink channel where linear transmission and reception strategy is employed. The base station (BS) transmitter is equipped with a scheduler using a simple opportunistic beamforming strategy, which associates an intended user for each of the transmitted data streams. For the case when the channel of the scheduled users is available at the BS, we propose a general method for joint design of the transmit and the receive beamformers according to different optimization criteria, including weighted sum rate maximization, weighted sum mean square error minimization, minimum signal-to-interference-plus-noise ratio (SINR) maximization and sum power minimization under a minimum SINR constraint. The proposed method can handle multiple antennas at the BS and at the mobile user with single and/or multiple data streams per scheduled user. The optimization problems encountered in the beamformer design (e.g., covariance rank constraint) are not convex in general. Therefore, the problem of finding the global optimum is intrinsically nontractable. However, by exploiting the uplink-downlink SINR duality, we decompose the original optimization problem as a series of simpler optimization problems which can be efficiently solved by using standard convex optimization tools. Even though each subproblem is optimally solved, there is no guarantee that the global optimum has been found due to the nonconvexity of the problem. However, the simulations show that the algorithms converge fast to a solution, which can be a local optimum, but is still efficient.