{"title":"Cooperative Beamforming Design for Multi-BS Integrated Sensing and Communication Systems","authors":"Peng Wang, Dongsheng Han, Xi Song","doi":"10.1049/cmu2.70015","DOIUrl":null,"url":null,"abstract":"<p>Integrated sensing and communication (ISAC) is regarded as a promising paradigm for future sixth-generation (6G) networks, which effectively improves spectral efficiency and reduces hardware costs by simultaneously performing communication and sensing. Due to the limited coverage of a single base station (BS), the single-BS ISAC system struggles to meet the demands of various emerging intelligent applications for high-quality communication and high-precision sensing. In this paper, we investigate a cooperative multi-BS ISAC system with multi-target and multi-user. In particular, communication and sensing are performed by multiple BSs with a cooperative manner. We formulate a problem for the purpose of maximizing the sensing mutual information (MI) via jointly designing the transmit beamforming of multiple BSs for communication and sensing, while guaranteeing the achievable communication rate requirements. To address this non-convex problem, an iterative optimization algorithm is developed based on the Lagrangian transform and the quadratic fractional transform. Simulation results validate the advancement of the proposed cooperative beamforming scheme in enhancing the sensing performance of multi-BS ISAC system.</p>","PeriodicalId":55001,"journal":{"name":"IET Communications","volume":"19 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/cmu2.70015","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Communications","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/cmu2.70015","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Integrated sensing and communication (ISAC) is regarded as a promising paradigm for future sixth-generation (6G) networks, which effectively improves spectral efficiency and reduces hardware costs by simultaneously performing communication and sensing. Due to the limited coverage of a single base station (BS), the single-BS ISAC system struggles to meet the demands of various emerging intelligent applications for high-quality communication and high-precision sensing. In this paper, we investigate a cooperative multi-BS ISAC system with multi-target and multi-user. In particular, communication and sensing are performed by multiple BSs with a cooperative manner. We formulate a problem for the purpose of maximizing the sensing mutual information (MI) via jointly designing the transmit beamforming of multiple BSs for communication and sensing, while guaranteeing the achievable communication rate requirements. To address this non-convex problem, an iterative optimization algorithm is developed based on the Lagrangian transform and the quadratic fractional transform. Simulation results validate the advancement of the proposed cooperative beamforming scheme in enhancing the sensing performance of multi-BS ISAC system.
期刊介绍:
IET Communications covers the fundamental and generic research for a better understanding of communication technologies to harness the signals for better performing communication systems using various wired and/or wireless media. This Journal is particularly interested in research papers reporting novel solutions to the dominating problems of noise, interference, timing and errors for reduction systems deficiencies such as wasting scarce resources such as spectra, energy and bandwidth.
Topics include, but are not limited to:
Coding and Communication Theory;
Modulation and Signal Design;
Wired, Wireless and Optical Communication;
Communication System
Special Issues. Current Call for Papers:
Cognitive and AI-enabled Wireless and Mobile - https://digital-library.theiet.org/files/IET_COM_CFP_CAWM.pdf
UAV-Enabled Mobile Edge Computing - https://digital-library.theiet.org/files/IET_COM_CFP_UAV.pdf