Proc. IEEE Asilomar Conference on Signals, Systems, and Computers, Oct. 30-Nov. 2, 2005, pp. 628-632.

Low Complexity User Selection Algorithms for Multiuser MIMO Systems with Block Diagonalization

Zukang Shen, Runhua Chen, Jeffrey G. Andrews, Robert W. Heath, Jr., and Brian L. Evans

Wireless Networking and Communications Group, The University of Texas at Austin, Austin, TX 78712 USA
shen@ece.utexas.edu - rhchen@ece.utexas.edu - jandrews@ece.utexas.edu - rheath@ece.utexas.edu - bevans@ece.utexas.edu

Paper Draft - Slides

Abstract

Block diagonalization (BD) is a precoding technique that eliminates inter-user interference in downlink multiuser multiple-input multiple-output (MIMO) systems. With the assumptions that all users have the same number of receive antennas and utilize all receive antennas when scheduled for transmission, the number of simultaneously supportable users with BD is limited by the ratio of the number of basestation transmit antennas to the number of user receive antennas. In a downlink MIMO system with a large number of users, the basestation may select a subset of users to serve in order to maximize the total throughput. The brute-force search for the optimal user set, however, is computationally prohibitive. We propose two low-complexity suboptimal user selection algorithms for multiuser MIMO systems with BD. Both algorithms aim to select a subset of users such that the total throughput is nearly maximized. The first user selection algorithm greedily maximizes the total throughput, whereas the criterion of the second algorithm is based on the channel energy. We show that both algorithms have linear complexity in the total number of users and achieve around 95% of the total throughput of the complete search method in simulations.


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Last Updated 02/21/06.