Sum Rate Optimization for MIMO Multicasting Network with Active IRS

IF 2.3 4区 计算机科学 Q1 Engineering International Journal of Distributed Sensor Networks Pub Date : 2023-10-11 DOI:10.1155/2023/5903661
Ping Li, Jinhong Bian
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Abstract

This paper considers a multiple-input multiple-output (MIMO) multicasting system aided by the intelligent reflecting surface (IRS). We aim to maximize the sum information rate via jointly designing the transmit precoding matrix and the reflecting coefficient (RC) matrix, subject to the transmit power constrains of the Tx and IRS. To tackle the nonconvex problem, we recast the original problem into an equivalent formulation by using some important facts about matrices and proposed a block coordinate descent (BCD) method to optimize the variables. Finally, simulation results validate the effectiveness of active IRS in enhancing the rate performance.
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具有有源IRS的MIMO多播网络的和速率优化
研究了一种基于智能反射面的多输入多输出多播系统。在不受发射功率限制的情况下,通过联合设计发射预编码矩阵和反射系数(RC)矩阵,实现信息总速率的最大化。为了解决非凸问题,利用矩阵的一些重要事实,将原问题转化为等价形式,提出了一种块坐标下降法(BCD)来优化变量。最后,仿真结果验证了有源IRS在提高速率性能方面的有效性。
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来源期刊
International Journal of Distributed Sensor Networks
International Journal of Distributed Sensor Networks Computer Science-Computer Networks and Communications
CiteScore
6.00
自引率
4.30%
发文量
94
审稿时长
11 weeks
期刊介绍: International Journal of Distributed Sensor Networks (IJDSN) is a JCR ranked, peer-reviewed, open access journal that focuses on applied research and applications of sensor networks. The goal of this journal is to provide a forum for the publication of important research contributions in developing high performance computing solutions to problems arising from the complexities of these sensor network systems. Articles highlight advances in uses of sensor network systems for solving computational tasks in manufacturing, engineering and environmental systems.
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