Dynamical ON-OFF Control with Trajectory Prediction for Multi-RIS Wireless Networks

Fuente: arXiv
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Autores principales: Wang, Kaining, Yang, Bo, Lei, Yusheng, Yu, Zhiwen, Cao, Xuelin, Alexandropoulos, George C., Di Renzo, Marco, Yuen, Chau
Formato: Preprint
Publicado: 2025
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author Wang, Kaining
Yang, Bo
Lei, Yusheng
Yu, Zhiwen
Cao, Xuelin
Alexandropoulos, George C.
Di Renzo, Marco
Yuen, Chau
author_facet Wang, Kaining
Yang, Bo
Lei, Yusheng
Yu, Zhiwen
Cao, Xuelin
Alexandropoulos, George C.
Di Renzo, Marco
Yuen, Chau
contents Reconfigurable intelligent surfaces (RISs) have demonstrated an unparalleled ability to reconfigure wireless environments by dynamically controlling the phase, amplitude, and polarization of impinging waves. However, as nearly passive reflective metasurfaces, RISs may not distinguish between desired and interference signals, which can lead to severe spectrum pollution and even affect performance negatively. In particular, in large-scale networks, the signal-to-interference-plus-noise ratio (SINR) at the receiving node can be degraded due to excessive interference reflected from the RIS. To overcome this fundamental limitation, we propose in this paper a trajectory prediction-based dynamical control algorithm (TPC) for anticipating RIS ON-OFF states sequence, integrating a long-short-term-memory (LSTM) scheme to predict user trajectories. In particular, through a codebook-based algorithm, the RIS controller adaptively coordinates the configuration of the RIS elements to maximize the received SINR. Our simulation results demonstrate the superiority of the proposed TPC method over various system settings.
format Preprint
id arxiv_https___arxiv_org_abs_2505_20887
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Dynamical ON-OFF Control with Trajectory Prediction for Multi-RIS Wireless Networks
Wang, Kaining
Yang, Bo
Lei, Yusheng
Yu, Zhiwen
Cao, Xuelin
Alexandropoulos, George C.
Di Renzo, Marco
Yuen, Chau
Networking and Internet Architecture
Signal Processing
Reconfigurable intelligent surfaces (RISs) have demonstrated an unparalleled ability to reconfigure wireless environments by dynamically controlling the phase, amplitude, and polarization of impinging waves. However, as nearly passive reflective metasurfaces, RISs may not distinguish between desired and interference signals, which can lead to severe spectrum pollution and even affect performance negatively. In particular, in large-scale networks, the signal-to-interference-plus-noise ratio (SINR) at the receiving node can be degraded due to excessive interference reflected from the RIS. To overcome this fundamental limitation, we propose in this paper a trajectory prediction-based dynamical control algorithm (TPC) for anticipating RIS ON-OFF states sequence, integrating a long-short-term-memory (LSTM) scheme to predict user trajectories. In particular, through a codebook-based algorithm, the RIS controller adaptively coordinates the configuration of the RIS elements to maximize the received SINR. Our simulation results demonstrate the superiority of the proposed TPC method over various system settings.
title Dynamical ON-OFF Control with Trajectory Prediction for Multi-RIS Wireless Networks
topic Networking and Internet Architecture
Signal Processing
url https://arxiv.org/abs/2505.20887