This paper investigates the use of beyond diagonal reconfigurable intelligent surface (BD-RIS) with N elements to advance integrated sensing and communication (ISAC). We address a key gap in the statistical characterizations of the radar signal-to-noise ratio (SNR) and the communication signal-to-interference-plus-noise ratio (SINR) by deriving tractable closed-form cumulative distribution functions (CDFs) for these metrics. Our approach maximizes the radar SNR by jointly configuring radar beamforming and BD-RIS phase shifts. Subsequently, zero-forcing is adopted to mitigate user interference, enhancing the communication SINR. To meet ISAC outage requirements, we propose an analytically-driven successive non-inversion sampling (SNIS) algorithm for estimating network parameters satisfying network outage constraints. Numerical results illustrate the accuracy of the derived CDFs and demonstrate the effectiveness of the proposed SNIS algorithm.
@article{arxiv.2502.12916,
title = {Beyond Diagonal RIS for ISAC Network: Statistical Analysis and Network Parameter Estimation},
author = {Thanh Luan Nguyen and Georges Kaddoum and Bassant Selim and Chadi Assi},
journal= {arXiv preprint arXiv:2502.12916},
year = {2025}
}