Genetic and Greedy User Scheduling for Multiuser MIMO Systems with Successive Zero-Forcing

In this paper we consider efficient and low complexity scheduling algorithms for multiuser multiple-input multiple-output (MIMO) systems. The optimal user scheduling involves an exhaustive search, which becomes very complex for realistic numbers of users and transmit antennas. Among various suboptimal but low complexity algorithms, greedy algorithms with heuristic scheduling metrics have been shown to achieve performance close to an exhaustive search. Meanwhile, genetic algorithms (GAs) are a rapid, though suboptimal, option of performing a utility (in this case scheduling) metric optimization. In this paper, we propose and analyze the performance and complexity of greedy and genetic scheduling algorithms for multiuser MIMO systems with successive zero-forcing preceding. We demonstrate that at lower K, the genetic algorithm performs better than the greedy algorithm, where K denotes the total number of users requesting service. For large K, however, the greedy algorithm outperforms the genetic algorithm. The greedy algorithm also achieves similar sum-rate growth (with K) as the exhaustive search. A detailed complexity analysis shows that the order of complexity of the genetic algorithm is higher than that of the greedy algorithm by a factor equal to K
₀

²
, where K
₀
denotes the maximum number of simultaneously served multiple-antenna users. Both algorithms achieve a sum rate very close to the exhaustive search with much less complexity for a small number of transmit antennas.