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

IF 3.2 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Zehua Yu;Haibo Zhao;Qinghua Guo;Jinshan Ding
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引用次数: 0

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.
将干扰转换为增益:通过非合作基站信号增强ISAC系统的感知能力
减少基站之间的干扰是综合传感和通信系统的一个重大挑战,特别是在非合作部署中。这封信调查了isac支持的基站受到来自另一个非合作基站(NBS)下行链路(DL)传输干扰的情况。我们观察到目标反射干扰包含有价值的信息,激励其开发,以提高传感能力。然而,如果没有导航信息,对NBS信号进行精确的符号估计是不可行的。为了解决这个问题,我们提出了一种新的迭代重建消除算法(IREA),该算法通过有效的一维搜索获得NBS信号的相位模糊估计,从而实现干扰缓解和从反射干扰信号中提取目标信息。仿真结果表明,该方法显著提高了目标检测和定位性能。
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来源期刊
IEEE Signal Processing Letters
IEEE Signal Processing Letters 工程技术-工程:电子与电气
CiteScore
7.40
自引率
12.80%
发文量
339
审稿时长
2.8 months
期刊介绍: The IEEE Signal Processing Letters is a monthly, archival publication designed to provide rapid dissemination of original, cutting-edge ideas and timely, significant contributions in signal, image, speech, language and audio processing. Papers published in the Letters can be presented within one year of their appearance in signal processing conferences such as ICASSP, GlobalSIP and ICIP, and also in several workshop organized by the Signal Processing Society.
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