Beyond Diagonal Intelligent Reflecting Surface Aided Integrated Sensing and Communication

Beyond diagonal intelligent reflecting surface (BD-IRS) is a new promising IRS architecture for which the reflection matrix is not limited to the diagonal structure as for conventional IRS. In this paper, we study a BD-IRS aided uplink integrated sensing and communication (ISAC) system where sensing is performed in a device-based manner. Specifically, we aim to estimate the unknown and random location of an active target based on its uplink probing signals sent to a multi-antenna base station (BS) as well as the known prior distribution information of the target’s location. Multiple communication users also simultaneously send uplink signals, resulting in a challenging mutual interference issue between sensing and communication. We first characterize the sensing performance metric by deriving the posterior Cramér-Rao bound (PCRB) of the mean-squared error (MSE) when prior information is available. Then, we formulate a BD-IRS reflection matrix optimization problem to maximize the minimum expected achievable rate among the multiple users subject to a constraint on the PCRB as well as the lossless and reciprocal constraints on the BD-IRS reflection matrix. The formulated problem is non-convex and challenging to solve. To tackle this problem, we propose a penalty dual decomposition (PDD) based algorithm which can find a high-quality suboptimal solution with polynomial-time complexity. In addition, we propose and optimize a time-division multiple access (TDMA) based scheme which removes the sensing-communication mutual interference. Numerical results verify the effectiveness of the proposed designs and provide useful design insights such as the optimal choice of multiple access scheme.