Converting Interference to Gain: Enhancing Sensing Capabilities of ISAC Systems via Noncooperative Base Station Signals

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.

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Publication Details

Journal
IEEE Signal Processing Letters
Published
2025-01-01
DOI
https://doi.org/10.1109/lsp.2025.3560904
Primary Topic
Target Tracking and Data Fusion in Sensor Networks
Type
article
Field-Weighted Citation Impact
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article

Converting Interference to Gain: Enhancing Sensing Capabilities of ISAC Systems via Noncooperative Base Station Signals

Zehua Yu, Jinshan Ding, Qinghua Guo, Haibo Zhao
IEEE Signal Processing Letters
Target Tracking and Data Fusion in Sensor Networks
article

Converting Interference to Gain: Enhancing Sensing Capabilities of ISAC Systems via Noncooperative Base Station Signals

Zehua Yu, Jinshan Ding, Qinghua Guo, Haibo Zhao
article en

Abstract

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.

IEEE Signal Processing LettersVol. 32
Xidian University (CN), University of Wollongong (AU)
Openalex Percentile: Top 97%
Target Tracking and Data Fusion in Sensor Networks
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Converting Interference to Gain: Enhancing Sensing Capabilities of ISAC Systems via Noncooperative Base Station Signals — Zehua Yu, Jinshan Ding, et al. · IEEE Signal Processing Letters (2025) | TGRS Research Map | TGRS