本研究针对网络式集成感知与通信（integrated sensing and communication, ISAC）系统展开研究，该系统中多个基站（base stations, BSs）通过容量受限的前传链路连接至中央处理器（central processor, CP），在协同服务通信用户的同时对目标进行感知。研究的核心目标是在满足通信与感知的信干噪比（signal-to-interference-plus-noise ratio, SINR）要求、且受限于前传容量约束的前提下，最小化总发射功率，由此构建了前传压缩与波束成形联合设计（joint fronthaul compression and beamforming design, J-FCBD）问题。\n我们证明最优前传压缩变量可与波束成形向量一并通过闭式解确定，这是该领域的一项全新发现。基于这一结论，我们证明剩余的波束成形设计问题可通过半定松弛（semidefinite relaxation, SDR）技术求得全局最优解，不过该方法计算复杂度较高。此外，其SDR的紧性表明所研究问题与其拉格朗日对偶问题之间不存在对偶间隙。\n基于该对偶性结果，我们利用ISAC框架下全新的上下行（UL-DL）对偶性，提出了一种高效的基于原始-对偶（primal-dual, PD）的算法。该算法交替执行两个步骤：在对偶变量固定时通过不动点迭代求解波束成形问题，以及通过二分法更新对偶变量；由于每步迭代的计算成本极低，该算法既能保证全局最优性，又具备很高的效率。数值仿真结果验证了所提PD基算法的全局最优性、有效性与高效性。
英文摘要：
This study investigates a networked integrated sensing and communication (ISAC) system, where multiple base stations (BSs), connected to a central processor (CP) via capacity-limited fronthaul links, cooperatively serve communication users while simultaneously sensing a target. The primary objective is to minimize the total transmit power while meeting the signal-to-interference-plus-noise ratio (SINR) requirements for communication and sensing under fronthaul capacity constraints, resulting in a joint fronthaul compression and beamforming design (J-FCBD) problem. We demonstrate that the optimal fronthaul compression variables can be determined in closed form alongside the beamformers, a novel finding in this field. Leveraging this insight, we show that the remaining beamforming design problem can be solved globally using the semidefinite relaxation (SDR) technique, albeit with considerable complexity. Furthermore, the tightness of its SDR reveals zero duality gap between the considered problem and its Lagrangian dual. Building on this duality result, we exploit the novel UL-DL duality within the ISAC framework to develop an efficient primal-dual (PD)-based algorithm. The algorithm alternates between solving beamforming with a fixed dual variable via fixed-point iteration and updating dual variable via bisection, ensuring global optimality and achieving high efficiency due to the computationally inexpensive iterations. Numerical results confirm the global optimality, effectiveness, and efficiency of the proposed PD-based algorithm.
Intelligent Reflecting Surfaces for Integrated Sensing and Communications: From System Coexistence to Networked Mutualism
Shanghai Jiao Tong University（上海交通大学）；University of Macau（澳门大学）；State Key Laboratory of Internet of Things for Smart City, University of Macau（澳门大学物联网智慧城市国家重点实验室）；University of Waterloo（滑铁卢大学）；Dalian University of Technology（大连理工大学）；Shenzhen University（深圳大学）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Shenzhen Future Network of Intelligence Institute (FNii-Shenzhen)（深圳未来网络智能研究所）
Coordinated Beamforming for Networked Integrated Communication and Multi-TMT Localization
National Mobile Communications Research Laboratory, Southeast University（东南大学国家移动通信重点实验室）；Purple Mountain Laboratories（紫金山实验室）；School of Electrical Engineering and Telecommunications, University of New South Wales（新南威尔士大学电气与电信工程学院）；Department of Electrical and Computer Engineering, the University of Texas at Dallas（德克萨斯大学达拉斯分校电气与计算机工程系）
Radar and wireless communication are widely acknowledged as the two most successful applications of the radio technology over the past decades. Recently, there is a trend in both academia and industry to achieve integrated sensing and communication (ISAC) in one system via utilizing a common radio spectrum and the same hardware platform. This article will discuss about the possibility of exploiting the future sixth-generation (6G) cellular network to realize ISAC. Our vision is that the cellular base stations (BSs) deployed all over the world can be transformed into a powerful sensor to provid…
IIIT Bangalore（印度信息科学与技术研究所班加罗尔分校）；IIITB COMET Foundation（IIITB COMET基金会）；ECE department at IIIT Bangalore（印度信息科学与技术研究所班加罗尔分校电子与计算机工程系）；IIT Roorkee（印度理工学院罗尔基分校）；ECE department at IIT Roorkee（印度理工学院罗尔基分校电子与计算机工程系）
Recently, there is a growing interest in achieving integrated sensing and communication (ISAC) in the sixth-generation (6G) cellular network. Inspired by this trend and the success of cooperative communication in cloud radio access network, this paper considers a networked device-free sensing architecture based on base station (BS) cooperation to transform the cellular network into a huge sensor that can provide ubiquitous and high-performance sensing services. Under this framework, the BSs first transmit the downlink communication signals to the mobile users and then estimate the range inform…
With the development of innovative applications that demand accurate environment information, e.g., autonomous driving, sensing becomes an important requirement for future wireless networks. To this end, integrated sensing and communication (ISAC) provides a promising platform to exploit the synergy between sensing and communication, where perceptive mobile networks (PMNs) were proposed to add accurate sensing capability to existing wireless networks. The well-developed cellular networks offer exciting opportunities for sensing, including large coverage, strong computation and communication po…
