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

  • Song, Chihyun
  • Lee, Donghyun
  • Lee, Yunseong
  • Noh, Wonjong
  • Cho, Sungrae
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초록

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. © 2025 The Authors

키워드

Cell-free massive multiple-input multiple-outputDeep reinforcement learningEnergy efficiencySimultaneous transmitting and reflecting reconfigurable intelligent surface
제목
Deep learning based energy-efficient transmission control for STAR-RIS aided cell-free massive MIMO networks
저자
Song, ChihyunLee, DonghyunLee, YunseongNoh, WonjongCho, Sungrae
DOI
10.1016/j.icte.2025.02.001
발행일
2025-04
유형
Article
저널명
ICT Express
11
2
페이지
341 ~ 347

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