Optimal RIS Placement in Multi-User MISO Systems with User Randomness

Fuente: arXiv
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Main Authors: Rajasekaran, Abhishek, Karbalayghareh, Mehdi, Ma, Xiaoyan, Love, David J., Brinton, Christopher G.
Format: Preprint
Published: 2025
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author Rajasekaran, Abhishek
Karbalayghareh, Mehdi
Ma, Xiaoyan
Love, David J.
Brinton, Christopher G.
author_facet Rajasekaran, Abhishek
Karbalayghareh, Mehdi
Ma, Xiaoyan
Love, David J.
Brinton, Christopher G.
contents It is well established that the performance of reconfigurable intelligent surface (RIS)-assisted systems critically depends on the optimal placement of the RIS. Previous works consider either simple coverage maximization or simultaneous optimization of the placement of the RIS along with the beamforming and reflection coefficients, most of which assume that the location of the RIS, base station (BS), and users are known. However, in practice, only the spatial variation of user density and obstacle configuration are likely to be known prior to deployment of the system. Thus, we formulate a non-convex problem that optimizes the position of the RIS over the expected minimum signal-to-interference-plus-noise ratio (SINR) of the system with user randomness, assuming that the system employs joint beamforming after deployment. To solve this problem, we propose a recursive coarse-to-fine methodology that constructs a set of candidate locations for RIS placement based on the obstacle configuration and evaluates them over multiple instantiations from the user distribution. The search is recursively refined within the optimal region identified in each stage to determine the final optimal region for RIS deployment. Detailed numerical results are presented to corroborate our findings.
format Preprint
id arxiv_https___arxiv_org_abs_2511_03998
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Optimal RIS Placement in Multi-User MISO Systems with User Randomness
Rajasekaran, Abhishek
Karbalayghareh, Mehdi
Ma, Xiaoyan
Love, David J.
Brinton, Christopher G.
Signal Processing
It is well established that the performance of reconfigurable intelligent surface (RIS)-assisted systems critically depends on the optimal placement of the RIS. Previous works consider either simple coverage maximization or simultaneous optimization of the placement of the RIS along with the beamforming and reflection coefficients, most of which assume that the location of the RIS, base station (BS), and users are known. However, in practice, only the spatial variation of user density and obstacle configuration are likely to be known prior to deployment of the system. Thus, we formulate a non-convex problem that optimizes the position of the RIS over the expected minimum signal-to-interference-plus-noise ratio (SINR) of the system with user randomness, assuming that the system employs joint beamforming after deployment. To solve this problem, we propose a recursive coarse-to-fine methodology that constructs a set of candidate locations for RIS placement based on the obstacle configuration and evaluates them over multiple instantiations from the user distribution. The search is recursively refined within the optimal region identified in each stage to determine the final optimal region for RIS deployment. Detailed numerical results are presented to corroborate our findings.
title Optimal RIS Placement in Multi-User MISO Systems with User Randomness
topic Signal Processing
url https://arxiv.org/abs/2511.03998