Converting Interference to Gain: Enhancing Sensing Capabilities of ISAC Systems via Noncooperative Base Station Signals
Zehua Yu, Haibo Zhao, Qinghua Guo, Jinshan Ding · IEEE Signal Processing Letters · 2025
Mitigation of interference between base stations (BSs) is a significant challenge in integrated sensing and communication (ISAC) systems, particularly in noncooperative deployments. This letter investigates the scenario where an ISAC-enabled BS experiences interference from downlink (DL) transmission of another noncooperative BS (NBS). We observe that target-reflected interference contains valuable information, motivating its exploitation to enhance sensing capability. However, precise symbol estimation of NBS signals is infeasible without pilot information. To address this, we propose a novel iterative reconstruction-elimination algorithm (IREA) that derives a phase-ambiguous estimate of NBS signals through an efficient one-dimensional search, thereby enabling both interference mitigation and target information extraction from the reflected interference signals. Simulations demonstrate significant improvements in target detection and localization performance through our interference exploitation method.