Beamforming Optimization for Full-Duplex Wireless-Powered MIMO Systems

被引:27
|
作者
Chalise, Batu Krishna [1 ,2 ]
Suraweera, Himal A. [3 ]
Zheng, Gan [4 ]
Karagiannidis, George K. [5 ]
机构
[1] New York Inst Technol, Dept Elect & Comp Engn, Old Westbury, NY 11568 USA
[2] Cleveland State Univ, Dept Elect Engn & Comp Sci, Cleveland, OH 44115 USA
[3] Univ Peradeniya, Dept Elect & Elect Engn, Peradeniya 20400, Sri Lanka
[4] Loughborough Univ, Wolfson Sch Mech Elect & Mfg Engn, Loughborough LE11 3TU, Leics, England
[5] Aristotle Univ Thessaloniki, Elect & Comp Engn Dept, Thessaloniki 54636, Greece
基金
英国工程与自然科学研究理事会;
关键词
Full-duplex; wireless power transfer; throughput; outage probability; convex optimization; SELF-INTERFERENCE; ACHIEVABLE RATES; COMMUNICATION; INFORMATION; NETWORKS;
D O I
10.1109/TCOMM.2017.2710196
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
We propose techniques for optimizing transmit beamforming in a full-duplex multiple-input-multiple-output wireless-powered communication system, which consists of two phases. In the first phase, the wireless-powered mobile station (MS) harvests energy using signals from the base station (BS), whereas in the second phase, both MS and BS communicate to each other in a full-duplex mode. When complete instantaneous channel state information (CSI) is available, the BS beamformer and the time-splitting (TS) parameter of energy harvesting are jointly optimized in order to obtain the BS-MS rate region. The joint optimization problem is non-convex, however, a computationally efficient optimum technique, based upon semidefinite relaxation and line-search, is proposed to solve the problem. A sub-optimum zero-forcing approach is also proposed, in which a closed-form solution of TS parameter is obtained. When only the second-order statistics of transmit CSI is available, we propose to maximize the ergodic information rate at the MS while maintaining the outage probability at the BS below a certain threshold. An upper bound for the outage probability is also derived and an approximate convex optimization framework is proposed for efficiently solving the underlying non-convex problem. Simulations demonstrate the advantages of the proposed methods over the sub-optimum and half-duplex ones.
引用
收藏
页码:3750 / 3764
页数:15
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