Intelligent Reflecting Surface Aided MIMO Cognitive Radio Systems
Intelligent Reflecting Surface Aided MIMO Cognitive Radio Systems
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DOI：
10.1109/tvt.2020.3011308
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发表时间：
2020-07
影响因子：
6.8
通讯作者：
Lei Zhang;Yu Wang;Weige Tao;Z. Jia;Tiecheng Song;Cunhua Pan
中科院分区：
文献类型：
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作者：
Lei Zhang;Yu Wang;Weige Tao;Z. Jia;Tiecheng Song;Cunhua Pan
在认知无线电（CR）系统中，辅助用户（su）的频谱效率（SE）总是受到主用户（pu）的干扰温度约束的限制。智能反射面（IRS）是近年来提出的一种革命性的技术，可以帮助提高无线通信的SE。在本文中，我们建议在多输入多输出（MIMO） CR系统中使用IRS来辅助su的数据传输。通过联合优化SU发射机（ST）的发射预编码（TPC）和IRS的相移，我们的目标是在ST的总功率、PU的干扰温度和单位模量约束下最大化SU的可实现加权和率（WSR）。为了解决这一复杂的变量耦合优化问题，引入了块坐标下降（BCD）算法交替求解子问题。对于每个子问题，采用复杂度较低的拉格朗日对偶或内逼近方法。仿真结果证实了在MIMO CR系统中采用IRS的优点。通过评估各种参数对WSR的影响，将所提出的算法与其他几个基准进行了性能比较。
In cognitive radio (CR) systems, the spectrum efficiency (SE) of the secondary users (SUs) is always limited by the interference temperature constraint imposed on the primary users (PUs). Intelligent reflecting surface (IRS) has been recently proposed as a revolutionary technique which can help to enhance the SE of wireless communications. In this paper, we propose to employ an IRS to assist the SUs’ data transmission in the multiple-input multiple-output (MIMO) CR system. By jointly optimizing the transmit precoding (TPC) of the SU transmitter (ST) and the phase shifts of the IRS, we aim to maximize the achievable weighted sum rate (WSR) of SUs subject to the ST's total power, the PU's interference temperature and unit modulus constraints. To solve this complicated optimization problem in which the variables are coupled, the block coordinate descent (BCD) algorithm is introduced to alternately solve the subproblems. For each subproblem, the Lagrange dual or inner approximation method is adopted with a low complexity. Simulation results confirm the benefits of employing IRS in a MIMO CR system. The performance comparisons of the proposed algorithm with several other benchmarks are carried out by evaluating the impacts of various parameters on the WSR.