Clutter-Aware Waveform Design for Multi-Cell Integrated Sensing and Communication Systems

Abstract

To address the challenges of inter-cell interference/reflection and static clutter, a clutter-aware waveform design for a multi-cell multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system is proposed. Various levels of coordination among base stations (BSs) are investigated to enhance target detectability in cluttered environments while maintaining the quality of service (QoS) for communication users. Specifically, two coordination schemes are investigated: 1) coordinated beamforming (CBF), where only channel state information (CSI) is shared, and 2) coordinated multipoint (CoMP), where both CSI and user data are exchanged among BSs. The waveform design problem is formulated as a non-convex optimization that maximizes the radar output signal-to-clutter-plus-interference-plus-noise ratio (SCINR), subject to robust symbol-level QoS and constant-modulus power constraints to ensure uncertainty in shared and estimated CSI. To tackle this problem, the single-ratio SCINR objective is decoupled via Dinkelbach’s transform (or a quadratic transform for multiple-ratio objectives) and reformulated on a Riemannian manifold to accommodate the constant-modulus constraint guarantees a practical peak-to-average-power ratio (PAPR). The resulting problem is further converted into an unconstrained form using the augmented Lagrangian method (ALM) and solved through a Riemannian conjugate gradient (RCG) algorithm. Simulation results demonstrate that the proposed designs achieve superior radar and communication performance compared to baseline schemes that underestimate the effects of multi-cell deployment.