Proportional Fair Scheduling Based on Genetic Algorithms for Multi-user MIMO Systems

Authors:
Peng Shang;Gang Su;Guangxi Zhu;Li Tan
Affiliations:
Department of Electronics & Information Engineering, Huazhong University of Science & Technology, Wuhan, P.R. China 430074;Department of Electronics & Information Engineering, Huazhong University of Science & Technology, Wuhan, P.R. China 430074;Department of Electronics & Information Engineering, Huazhong University of Science & Technology, Wuhan, P.R. China 430074;Department of Electronics & Information Engineering, Huazhong University of Science & Technology, Wuhan, P.R. China 430074
Venue:
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II
Year:
2009

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Abstract

For the resource allocation and scheduling of downlink multi-user multiple input multiple output (MU-MIMO) system, a multi-user proportional fair scheduling scheme based on genetic algorithms (GA) is proposed. By adding some good-gene individuals to the initial population and keeping its gene stable, the convergence of GA is greatly accelerated. Specifically, the base station exploits Block Diagonalization (BD) precoding technique to eliminate the inter-user interference. To guarantee the fairness while maintaining the throughput performance, a subset of users is selected to serve at one time slot. Moreover, the impact of feedback error on the channel state information is analyzed. Simulation results show that both schemes can achieve a good tradeoff between fairness and throughput with low computational complexity compared to other scheduling schemes.