Full-Duplex ISAC-Enabled D2D Underlaid Cellular Networks: Joint Transceiver Beamforming and Power Allocation

IF 8 1区计算机科学 Q1 TELECOMMUNICATIONS

IEEE Transactions on Cognitive Communications and Networking Pub Date : 2026-01-01 Epub Date: 2025-03-18 DOI:10.1109/TCCN.2025.3552627

Tao Jiang;Ming Jin;Qinghua Guo;Yinhong Liu;Yaming Li;Junteng Yao

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引用次数: 0

Abstract

Integrating device-to-device (D2D) communication into cellular networks can significantly reduce the transmission burden on base stations (BSs). Besides, integrated sensing and communication (ISAC) is envisioned as a key feature in future wireless networks. In this work, we consider a full-duplex ISAC-based D2D underlaid system, and propose a joint beamforming and power allocation scheme to improve the performance of the coexisting ISAC and D2D networks. To enhance spectral efficiency, a sum rate maximization problem is formulated for the full-duplex ISAC-based D2D underlaid system, which is non-convex. To solve the non-convex optimization problem, we propose a successive convex approximation (SCA)-based iterative algorithm and prove its convergence. Numerical results are provided to validate the effectiveness of the proposed scheme with the iterative algorithm, demonstrating that the proposed scheme outperforms state-of-the-art ones in both communication and sensing performance.

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全双工isac支持的D2D底层蜂窝网络：联合收发器波束形成和功率分配

将设备对设备（D2D）通信集成到蜂窝网络中可以显著减少基站（BSs）的传输负担。此外，集成传感和通信（ISAC）被设想为未来无线网络的一个关键特征。在这项工作中，我们考虑了基于ISAC的全双工D2D底层系统，并提出了一种联合波束形成和功率分配方案，以提高共存ISAC和D2D网络的性能。为了提高频谱效率，提出了基于isac的全双工非凸D2D底层系统的和速率最大化问题。为了解决非凸优化问题，提出了一种基于连续凸逼近（SCA）的迭代算法，并证明了其收敛性。数值结果验证了该算法的有效性，表明该算法在通信和感知性能上都优于现有算法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Cognitive Communications and Networking Computer Science-Artificial Intelligence

CiteScore

15.50

自引率

7.00%

发文量

108

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.