*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.