Integrated sensing and communication (ISAC) has emerged as a key technology for future communication systems. In this paper, we provide a general framework to reveal the fundamental tradeoff between sensing and communication in OFDM systems, where a unified ISAC waveform is exploited to perform both tasks. In particular, we define the Capacity-Bayesian Cramer Rao Bound (BCRB) region in the asymptotically case when the number of subcarriers is large. Specifically, we show that the asymptotically optimal input distribution that achieves the Pareto boundary point of the Capacity-BCRB region is Gaussian and the entire Pareto boundary can be obtained by solving a convex power allocation problem. Moreover, we characterize the structure of the sensing-optimal power allocation in the asymptotically case. Finally, numerical simulations are conducted to verify the theoretical analysis and provide useful insights.
CP-OFDM Achieves Lower Ranging CRB Than Frequency-Spread Waveforms in the Large-Sample Regime
National Mobile Communications Research Laboratory, Southeast University（东南大学国家移动通信实验室）；Department of Communication Engineering, Beijing University of Posts and Telecommunications（北京邮电大学通信工程系）；Ministry of Education Key Laboratory of Mathematics and Information Networks, School of Mathematical Sciences, Beijing University of Posts and Telecommunications（北京邮电大学数学科学学院数学与信息网络教育部重点实验室）；Frontiers Science Center for Mobile Information Communication and Security, Southeast University（东南大学移动信息通信与安全前沿科学中心）；Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Southeast University（东南大学复杂系统测量与控制教育部重点实验室）；Department of Electrical and Electronic Engineering, University College London（伦敦大学学院电气与电子工程系）
This paper studies a multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system, in which a multi-antenna base station (BS) sends unified wireless signals to estimate an extended target and communicate with a multi-antenna communication user (CU) at the same time. We investigate the fundamental tradeoff between the estimation Cramér-Rao bound (CRB) for sensing and the data rate for communication, by characterizing the Pareto boundary of the achievable CRB-rate (C-R) region. Towards this end, we formulate a new MIMO rate maximization problem by optimizing the trans…
This paper studies a multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system, in which a multi-antenna base station (BS) sends unified wireless signals to estimate one sensing target and communicate with a multi-antenna communication user (CU) simultaneously. We consider both the point and extended target models. For the point target case, the BS estimates the target angle and we adopt the Cramér-Rao bound (CRB) for angle estimation as the sensing performance metric. For the extended target case, the BS estimates the complete target response matrix, and we cons…
This paper studies the multi-antenna multicast channel with integrated sensing and communication (ISAC), in which a multi-antenna base station (BS) sends common messages to a set of single-antenna communication users (CUs) and simultaneously estimates the parameters of an extended target via radar sensing. We investigate the fundamental performance limits of this ISAC system, in terms of the achievable rate for communication and the estimation Cramér-Rao bound (CRB) for sensing. First, we derive the optimal transmit covariance in semi-closed form to balance the CRB-rate (C-R) tradeoff, and acc…
In cognitive radio (CR) networks, secondary users (SUs) are allowed to opportunistically access the primary users (PUs) spectrum to improve the spectrum utilization; however, this increases the interference levels at the PUs. In this paper, we consider an orthogonal frequency division multiplexing OFDM-based CR network and investigate the tradeoff between increasing the SU transmission rate (hence improving the spectrum utilization) and reducing the interference levels at the PUs. We formulate a new multiobjective optimization (MOOP) problem that jointly maximizes the SU transmission rate and …
In dual-functional communication-radar systems, common radio frequency (RF) signals are used for both communication and detection. For better compatibility with existing communication systems, we adopt multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) signals as integrated signals and investigate the estimation performance of MIMO-OFDM signals. We first analyze the Cramer-Rao lower bound (CRLB) of parameters estimation. Then, transmit powers over different subcarriers are optimized to achieve the best tradeoff between transmission rate and estimation perfo…
The problem of joint power and sub-channel allocation to maximize energy efficiency (EE) and spectral efficiency (SE) simultaneously in in-band full-duplex (IBFD) orthogonal frequency-division multiple access (OFDMA) network is addressed considering users' QoS in both uplink and downlink. The resulting optimization problem is a non-convex mixed-integer non-linear program (MINLP) which is generally difficult to solve. In order to strike a balance between the EE and SE, we restate this problem as a multi-objective optimization problem (MOOP) which aims at maximizing system's throughput and minim…
This paper unifies integrated sensing and communication (ISAC) and simultaneous wireless information and power transfer (SWIPT), by investigating a new multi-functional multiple-input multiple-output (MIMO) system integrating wireless sensing, communication, and powering. In this system, one multi-antenna hybrid access point (H-AP) transmits wireless signals to communicate with one multi-antenna information decoding (ID) receiver, wirelessly charge one multi-antenna energy harvesting (EH) receiver, and perform radar sensing for a point target based on the echo signal at the same time. Under th…
Xidian University（西安电子科技大学）；Southeast University（东南大学）；Information Engineering University（信息工程大学）；Peng Cheng Laboratory（鹏城实验室）；University of New South Wales（新南威尔士大学）
Joint Antenna Geometry and Transmit Covariance Design for Near-Field Multicast ISAC with Pinching Antenna Arrays
Hunan Institute of Science and Technology（湖南理工学院）；Hunan Institute of Engineering（湖南工程学院）；Donghua University（东华大学）；Laval University（拉瓦尔大学）；University of Saskatchewan（萨斯喀彻温大学）；Henan Polytechnic University（河南理工大学）
Extended Target Adaptive Beamforming for ISAC:A Perspective of Predictive Error Ellipse
Nanjing University（南京大学）；School of Intelligent Software and Engineering, Nanjing University (Suzhou Campus)（南京大学智能软件与工程学院（苏州校区））；Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China（电子科技大学长三角研究院（衢州））；University College London（伦敦大学学院）；Yonsei Frontier Laboratory, Yonsei University（延世大学延世前沿实验室）；Yonsei University（延世大学）
Performance Analysis for ISAC Systems with 1-bit DACs
School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology（皇家理工学院电气工程和计算机学院）；Department of Electrical-Electronics Engineering, TOBB University of Economics and Technology（TOBB经济与技术大学电气电子工程系）
