Message Passing based Parameter Estimation in Cooperative MIMO-OFDM ISAC Systems

In integrated sensing and communication (ISAC) networks, multiple base stations (BSs) collaboratively sense a common target, leveraging diversity from multiple observation perspectives and joint signal processing to enhance sensing performance. This paper introduces a novel message-passing (MP)-based parameter estimation framework for collaborative MIMO-OFDM ISAC systems, which jointly estimates the target's position and velocity. First, a signal propagation model is established based on geometric relationships, and a factor graph is constructed to represent the unknown parameters. The sum-product algorithm (SPA) is then applied to this factor graph to jointly estimate the multi-dimensional parameter vector. To reduce communication overhead and computational complexity, we employ a hierarchical message-passing scheme with Gaussian approximation. By adopting parameterized message distributions and layered processing, the proposed method significantly reduces both computational complexity and inter-BS communication overhead. Simulation results demonstrate the effectiveness of the proposed MP-based parameter estimation algorithm and highlight the benefits of multi-perspective observations and joint signal processing for cooperative sensing in MIMO-OFDM ISAC systems.

Target Detection in OFDM-ISAC Systems: A Multipath Exploitation Approach

This paper investigates the potential of multipath exploitation for enhancing target detection in orthogonal frequency division multiplexing (OFDM)-based integrated sensing and communication (ISAC) systems. The study aims to improve target detection performance by harnessing the diversity gain in the delay-Doppler domain. We propose a weighted generalized likelihood ratio test (GLRT) detector that effectively leverages the multipath propagation between the base station (BS) and the target. To further enhance detection accuracy, a joint optimization framework is developed for subcarrier power allocation at the transmitter and weight coefficients of the GLRT detector. The objective is to maximize the probability of target detection while satisfying constraints on total transmit power and the communication receiver's signal-to-noise ratio (SNR). An iterative algorithm based on the majorization-minimization (MM) method is employed to address the resulting non-convex optimization problem. Simulation results demonstrate the efficacy of the proposed algorithm and confirm the benefits of multipath exploitation for target detection in OFDM-ISAC systems under multipath-rich environments.