Xiangrong Wang;Weitong Zhai;Xianghua Wang;Moeness G. Amin;Kaiquan Cai
{"title":"Wideband Near-Field Integrated Sensing and Communication With Sparse Transceiver Design","authors":"Xiangrong Wang;Weitong Zhai;Xianghua Wang;Moeness G. Amin;Kaiquan Cai","doi":"10.1109/JSTSP.2024.3394970","DOIUrl":null,"url":null,"abstract":"With the deployment of extremely large-scale array (XL-array) operating at the high frequency bands in future wireless systems, integrated sensing and communication (ISAC) is expected to function in the electromagnetic near-field region with a potential distance of hundreds of meters. Also, a wide signal bandwidth is employed to benefit both communication capacity and sensing resolution. However, most existing works assume a far-field narrowband model, which has prohibited their practical applications in future ISAC systems. In this article, we propose a near-field wideband ISAC framework for concurrent multi-user downlink communications and multi-target localization. In particular, the expression of Cramer Rao Bound (CRB) of direction-of-arrival (DOA) and distance estimations for sensing multiple wideband sources is derived, which is minimized subject to the guaranteed communication quality of service (QoS) for each user. Based on the proposed ISAC framework, sparse transceiver array and the precoding matrix are jointly optimized to reduce mutual coupling and system overhead. The problem is relaxed to a convex optimization and solved iteratively. Simulation results demonstrate that the proposed wideband near-field ISAC framework can well support both modalities and that the sparse transceiver improves the sensing accuracy without sacrificing the communication performance.","PeriodicalId":13038,"journal":{"name":"IEEE Journal of Selected Topics in Signal Processing","volume":"18 4","pages":"662-677"},"PeriodicalIF":8.7000,"publicationDate":"2024-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Selected Topics in Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10521567/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
With the deployment of extremely large-scale array (XL-array) operating at the high frequency bands in future wireless systems, integrated sensing and communication (ISAC) is expected to function in the electromagnetic near-field region with a potential distance of hundreds of meters. Also, a wide signal bandwidth is employed to benefit both communication capacity and sensing resolution. However, most existing works assume a far-field narrowband model, which has prohibited their practical applications in future ISAC systems. In this article, we propose a near-field wideband ISAC framework for concurrent multi-user downlink communications and multi-target localization. In particular, the expression of Cramer Rao Bound (CRB) of direction-of-arrival (DOA) and distance estimations for sensing multiple wideband sources is derived, which is minimized subject to the guaranteed communication quality of service (QoS) for each user. Based on the proposed ISAC framework, sparse transceiver array and the precoding matrix are jointly optimized to reduce mutual coupling and system overhead. The problem is relaxed to a convex optimization and solved iteratively. Simulation results demonstrate that the proposed wideband near-field ISAC framework can well support both modalities and that the sparse transceiver improves the sensing accuracy without sacrificing the communication performance.
期刊介绍:
The IEEE Journal of Selected Topics in Signal Processing (JSTSP) focuses on the Field of Interest of the IEEE Signal Processing Society, which encompasses the theory and application of various signal processing techniques. These techniques include filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals using digital or analog devices. The term "signal" covers a wide range of data types, including audio, video, speech, image, communication, geophysical, sonar, radar, medical, musical, and others.
The journal format allows for in-depth exploration of signal processing topics, enabling the Society to cover both established and emerging areas. This includes interdisciplinary fields such as biomedical engineering and language processing, as well as areas not traditionally associated with engineering.