Max-Min Fairness in IRS-Aided MISO Broadcast Channel via Joint Transmit and Reflective Beamforming
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DOI码：10.1109/GLOBECOM42002.2020.9348016
所属单位：School of ComputerScience and Information Engineering, Hefei University of Technology
发表刊物：GLOBECOM 2020 - 2020 IEEE Global Communications Conference
项目来源：National Natural Science Foundation of China under Grants 61971176, and 61901156, Anhui Provincial
关键字：Intelligent reflecting surfaces, broadcast channel, reflective beamforming
摘要：The potential application of intelligent reflecting surfaces (IRSs) for future wireless cellular communication systems has motivated the study of metasurface for achieving additional space degree of freedom, where IRS is used to enhance the desired signal strength and suppress the interference. In this paper, by using the additional design degree of freedom provided by the IRS, we jointly optimize the transmit beamforming vector at the BS and the reflective beamforming vector at the IRS to maximize the minimum rate in the IRS-aided multi-user multiple-inputsingle-output broadcast channel (MISO-BC), subject to the unit modulus constraints of the reflective beamforming vector. In order to solve the non-convex optimization problem, we propose an efficient algorithm based on alternating optimization. In particular, we optimize the transmit beamforming vectors via the second-order cone problem (SOCP) and reflective beamforming vector by using the semi-definite relaxation (SDR). Numerical results show that the use of IRS leads to significant higher SINR values than benchmark schemes without IRS."
合写作者：Wenqi Ding,Wei Huang
第一作者：Caihong Kai
论文类型：会议
学科门类：工学
文献类型：C
ISSN号：2576-6813
是否译文：否
发表时间：2020-12-07
收录刊物：EI