RIS-Assisted Radar-Communication Coexistence: Detection Analysis with Channel Uncertainties
Abstract
Reconfigurable intelligent surfaces (RISs) have emerged as a promising technology for improving communication reliability in radar-communication coexistence (RCC) scenarios, particularly for communication users (CUs) located inside radar exclusion zones, where only the radar is permitted to operate and the two systems remain uncoordinated. In such settings, CUs may suffer from strong radar interference whose phase is random and difficult to track while also facing difficulty in obtaining accurat...
Description / Details
Reconfigurable intelligent surfaces (RISs) have emerged as a promising technology for improving communication reliability in radar-communication coexistence (RCC) scenarios, particularly for communication users (CUs) located inside radar exclusion zones, where only the radar is permitted to operate and the two systems remain uncoordinated. In such settings, CUs may suffer from strong radar interference whose phase is random and difficult to track while also facing difficulty in obtaining accurate CSI from the base station. These challenges become even more critical in the presence of RIS phase errors, which limit the applicability of conventional coherent detection methods. Motivated by these practical limitations, this paper develops an RIS-assisted RCC framework for a CU operating in an uncoordinated RCC setting. Within this framework, we derive two practical maximum-likelihood (ML)-based detectors, both of which avoid tracking the radar interference phase: 1) a non-coherent detector that does not require instantaneous CSI and incorporates RIS phase uncertainty, and 2) a mismatched coherent detector that relies on imperfect CSI. For the non-coherent case, we derive an exact likelihood expression and a closed-form detector in the low to moderate SINR regime. For the imperfect CSI case, we derive the corresponding closed-form detector in the low-to-moderate SINR regime, and analyze performance through pairwise error probability (PEP), yielding a tractable approximation based on Gauss-Chebyshev quadrature. Numerical and analytical results show that the proposed non-coherent detector closely matches the optimal ML detector, validating its practical usefulness.
Source: arXiv:2608.23422v1 - http://arxiv.org/abs/2608.23422v1 PDF: https://arxiv.org/pdf/2608.23422v1 Original Link: http://arxiv.org/abs/2608.23422v1
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Aug 25, 2026
Chemical Engineering
Engineering
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