Related papers: Joint Active RIS Configuration and User Power Control for Localization: A Neuroevolution-Based Approach

Joint Active RIS Configuration and User Power Control for Localization: A Neuroevolution-Based Approach

URL: http://arxiv.org/abs/2510.13819v1
Date: Thu, 25 Sep 2025 07:36:04 GMT
Title: Joint Active RIS Configuration and User Power Control for Localization: A Neuroevolution-Based Approach
Authors: George Stamatelis, Hui Chen, Henk Wymeersch, George C. Alexandropoulos,
Abstract summary: The paper studies user localization aided by a Reconfigurable Intelligent Surface (RIS)<n>A feedback link from the Base Station to the user is adopted to enable dynamic power control of the user pilot transmissions in the uplink.<n>A novel multi-agent algorithm for the joint control of the RIS phase configuration and the user transmit power is presented.
Score: 49.48992202227772
License: http://creativecommons.org/licenses/by/4.0/
Abstract: This paper studies user localization aided by a Reconfigurable Intelligent Surface (RIS). A feedback link from the Base Station (BS) to the user is adopted to enable dynamic power control of the user pilot transmissions in the uplink. A novel multi-agent algorithm for the joint control of the RIS phase configuration and the user transmit power is presented, which is based on a hybrid approach integrating NeuroEvolution (NE) and supervised learning. The proposed scheme requires only single-bit feedback messages for the uplink power control, supports RIS elements with discrete responses, and is numerically shown to outperform fingerprinting, deep reinforcement learning baselines and backpropagation-based position estimators.

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