JOINT ACTIVE RIS CONFIGURATION AND USER POWER CONTROL FOR LOCALIZATION: A NEUROEVOLUTION-BASED APPROACH
George Stamatelis, Hui Chen, George Alexandropoulos
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.
BibTeX
@inproceedings{icassp2026_jointactiverisco,
title = {JOINT ACTIVE RIS CONFIGURATION AND USER POWER CONTROL FOR LOCALIZATION: A NEUROEVOLUTION-BASED APPROACH},
author = {George Stamatelis and Hui Chen and George Alexandropoulos},
booktitle = {ICASSP 2026},
year = {2026}
}