Deep learning based energy-efficient transmission control for STAR-RIS aided cell-free massive MIMO networks

IF 4.1 3区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Chihyun Song , Donghyun Lee , Yunseong Lee , Wonjong Noh , Sungrae Cho
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引用次数: 0

Abstract

Recently, the simultaneous transmitting and reflecting (STAR) reconfigurable intelligent surface (RIS) has been gaining attention as a key enabler for sixth-generation networks, providing additional links with reduction in power consumption. This paper investigates the STAR-RIS’s potential in a cell-free (CF) massive multiple-input multiple-output (mMIMO) network, where distributed APs serve user over the same time/frequency. We propose a deep deterministic policy gradient framework satisfying system-specific and per-user spectral efficiency constraints, exploiting a post-normalization and a penalized reward. From the simulations, it is revealed the proposed algorithm provides better energy performance than benchmarks, highlighting the benefits of STAR-RIS in the CF network.
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来源期刊
ICT Express
ICT Express Multiple-
CiteScore
10.20
自引率
1.90%
发文量
167
审稿时长
35 weeks
期刊介绍: The ICT Express journal published by the Korean Institute of Communications and Information Sciences (KICS) is an international, peer-reviewed research publication covering all aspects of information and communication technology. The journal aims to publish research that helps advance the theoretical and practical understanding of ICT convergence, platform technologies, communication networks, and device technologies. The technology advancement in information and communication technology (ICT) sector enables portable devices to be always connected while supporting high data rate, resulting in the recent popularity of smartphones that have a considerable impact in economic and social development.
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