Machine Learning and Intelligent Communications. Second International Conference, MLICOM 2017, Weihai, China, August 5-6, 2017, Proceedings, Part II

Research Article

Joint Mode Selection and Beamformer Optimization for Full-Duplex Cellular Systems

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  • @INPROCEEDINGS{10.1007/978-3-319-73447-7_28,
        author={Fangni Chen and Jingyu Hua and Weidang Lu and Zhongpeng Wang},
        title={Joint Mode Selection and Beamformer Optimization for Full-Duplex Cellular Systems},
        proceedings={Machine Learning and Intelligent Communications. Second International Conference, MLICOM 2017, Weihai, China, August 5-6, 2017, Proceedings, Part II},
        proceedings_a={MLICOM},
        year={2018},
        month={2},
        keywords={Full-duplex Cellular system Self-interference Mode selection WSR},
        doi={10.1007/978-3-319-73447-7_28}
    }
    
  • Fangni Chen
    Jingyu Hua
    Weidang Lu
    Zhongpeng Wang
    Year: 2018
    Joint Mode Selection and Beamformer Optimization for Full-Duplex Cellular Systems
    MLICOM
    Springer
    DOI: 10.1007/978-3-319-73447-7_28
Fangni Chen,*, Jingyu Hua1,*, Weidang Lu1,*, Zhongpeng Wang2,*
  • 1: Zhejiang University of Technology
  • 2: Zhejiang University of Science and Technology
*Contact email: cfnini@163.com, eehjy@zjut.edu.cn, luweid@zjut.edu.cn, zhongpengwang@sohu.com

Abstract

We investigate a novel mode selection scheme for full-duplex (FD) cellular system where the base station (BS) and the user equipments (UEs) are equipped with multiple-input multiple-output (MIMO) antennas. We consider that FD is utilized at the BS, i.e. it enables simultaneous transmission and reception at the same frequency band, while UEs work in the conventional half-duplex (HD) way. Since FD system can not always outperform HD system due to residual self interference (RSI) at the base station, the mode selection is mainly determined by system performance. To address this issue, a joint mode selection and beamformer optimization problem with power constraints is formulated to achieve the maximal weighted sum rate (WSR). On account of the non-convex of original problem, a heuristic algorithm based on decoupling is proposed, which decomposes the original problem into two sub-problems. One is mode selection sub-problem and the other one is mean square error (MSE) minimization sub-problem. By means of simulation, the proposed algorithm shows the ability to choose the mode with greater performance in achievable rate.