Uplink Collaborative Sensing with OFDM Communication Signals

This paper addresses the resource allocation optimization problem in an uplink OFDM-based integrated sensing and communications (ISAC) network, where several multiple access points (APs) communicate with a base station (BS) and collaborate on target localization simultaneously. The goal is to minimize the Cramer-Rao Lower Bound (CRLB) for target position estimation while ensuring that communication quality of service (QoS) requirements. This is achieved by assigning orthogonal subcarriers to the APs and optimizing power allocation across these subcarriers. Given the complexity of the mixed-integer optimization problem, we propose an efficient alternating optimization algorithm incorporating successive convex approximation (SCA) method to iteratively obtain near-optimal solutions. Numerical simulations show that the proposed algorithm significantly improves the sensing performance compared to conventional uniform power allocation and communicationonly power allocation schemes. These findings underscore the effectiveness of the proposed approach in achieving a balance between communication and sensing objectives in ISAC systems.