{"title":"CRB-Rate Tradeoff in RSMA-Enabled Near-Field Integrated Multi-Target Sensing and Multi-User Communications","authors":"Jiasi Zhou;Cong Zhou;Yanjing Sun;Chintha Tellambura","doi":"10.1109/TCCN.2025.3587818","DOIUrl":null,"url":null,"abstract":"Near-field integrated sensing and communication (NF-ISAC) combines wireless communication with simultaneous angle and distance sensing. However, this dual functionality creates a complex interference environment. Existing NF-ISAC designs offer limited flexibility in managing such interference, highlighting the need for more advanced strategies. To address this, we propose a rate-splitting multiple access (RSMA) scheme for NF-ISAC, leveraging both fully and partially connected hybrid analog-digital (HAD) beamforming architectures. We derive the Cramér-Rao bound (CRB) for joint distance and angle sensing and characterize the tradeoff between the max-min communication rate and multi-target CRB. To explore the CRB-rate Pareto boundary, we formulate a sensing-centric optimization problem under communication rate constraints. For the fully connected HAD architecture, a penalty dual decomposition (PDD)-based double-loop algorithm is developed, while a two-stage approach is used to reduce complexity. This framework is also extended to the partially connected case. Simulations show that the proposed schemes achieve performance comparable to a fully digital beamformer with fewer RF chains, effectively balancing hardware efficiency and system performance. Furthermore, the schemes significantly outperform space division multiple access and far-field ISAC, delivering lower sensing error and an expanded CRB-rate region.","PeriodicalId":13069,"journal":{"name":"IEEE Transactions on Cognitive Communications and Networking","volume":"12 ","pages":"3687-3700"},"PeriodicalIF":8.0000,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Cognitive Communications and Networking","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11077707/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/10 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Near-field integrated sensing and communication (NF-ISAC) combines wireless communication with simultaneous angle and distance sensing. However, this dual functionality creates a complex interference environment. Existing NF-ISAC designs offer limited flexibility in managing such interference, highlighting the need for more advanced strategies. To address this, we propose a rate-splitting multiple access (RSMA) scheme for NF-ISAC, leveraging both fully and partially connected hybrid analog-digital (HAD) beamforming architectures. We derive the Cramér-Rao bound (CRB) for joint distance and angle sensing and characterize the tradeoff between the max-min communication rate and multi-target CRB. To explore the CRB-rate Pareto boundary, we formulate a sensing-centric optimization problem under communication rate constraints. For the fully connected HAD architecture, a penalty dual decomposition (PDD)-based double-loop algorithm is developed, while a two-stage approach is used to reduce complexity. This framework is also extended to the partially connected case. Simulations show that the proposed schemes achieve performance comparable to a fully digital beamformer with fewer RF chains, effectively balancing hardware efficiency and system performance. Furthermore, the schemes significantly outperform space division multiple access and far-field ISAC, delivering lower sensing error and an expanded CRB-rate region.
期刊介绍:
The IEEE Transactions on Cognitive Communications and Networking (TCCN) aims to publish high-quality manuscripts that push the boundaries of cognitive communications and networking research. Cognitive, in this context, refers to the application of perception, learning, reasoning, memory, and adaptive approaches in communication system design. The transactions welcome submissions that explore various aspects of cognitive communications and networks, focusing on innovative and holistic approaches to complex system design. Key topics covered include architecture, protocols, cross-layer design, and cognition cycle design for cognitive networks. Additionally, research on machine learning, artificial intelligence, end-to-end and distributed intelligence, software-defined networking, cognitive radios, spectrum sharing, and security and privacy issues in cognitive networks are of interest. The publication also encourages papers addressing novel services and applications enabled by these cognitive concepts.