In this letter, we study the parameter estimation performance for monostatic downlink integrated sensing and communications (ISAC) systems. In particular, we analyze the mean squared error (MSE) lower bound for target sensing in the downlink ISAC system that reveals the suboptimality in re-using the conventional communication waveform for sensing. To realize a practical dual-functional waveform, we propose a waveform augmentation strategy that imposes an extra signal structure, namely the degrees-of-freedom (DoF) completion method. The proposed approach is capable of improving the parameter estimation performance of the ISAC system and achieving the derived MSE lower bound. To improve the performance of the proposed strategy, we formulate an MSE minimization problem to design the ISAC precoder, subject to the communication users' signal-interference-plus-noise-ratio (SINR) constraints. Despite the non-convexity of the waveform design problem, we obtain its globally optimal solution via semi-definite relaxation (SDR) and the proposed constructive method. Simulation results validate the proposed DoF completion technology could achieve the derived MSE lower bound and the effectiveness of the MSE-based ISAC waveform design.
The degrees of freedom (DoFs) attained in monostatic integrated sensing and communications (ISAC) are analyzed. Specifically, monostatic sensing aims for extracting target-orientation information from the line of sight (LoS) channel between the transmitter and the target, since the Non-LoS (NLoS) paths only contain clutter or interference. By contrast, in wireless communications, typically, both the LoS and NLoS paths are exploited for achieving diversity or multiplexing gains. Hence, we shed light on the NLoS exploitation vs. reduction tradeoffs in a monostatic ISAC scenario. In particular, w…
Fusion of Monostatic and Bistatic Sensing for ISAC-Enabled Low-Altitude Environment Mapping
School of Information Science and Electronic Engineering, Shanghai Jiao Tong University（上海交通大学信息科学与工程学院）；Nantong University（南通大学）；School of Transportation and Civil Engineering, Nantong University（南通大学交通与土木工程学院）；State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications（北京邮电大学网络与交换技术国家重点实验室）
The collaborative sensing of multiple Integrated sensing and communication (ISAC) base stations is one of the important technologies to achieve intelligent transportation. Interference elimination between ISAC base stations is the prerequisite for realizing collaborative sensing. In this paper, we focus on the mutual interference elimination problem in collaborative sensing of multiple ISAC base stations that can communicate and radar sense simultaneously by transmitting ISAC signals. We establish a mutual interference model of multiple ISAC base stations, which consists of communication and r…
In this paper, we present a novel reconfigurable intelligent surface (RIS)-assisted integrated sensing and communication (ISAC) system with 1-bit quantization at the ISAC base station. An RIS is introduced in the ISAC system to mitigate the effects of coarse quantization and to enable the co-existence between sensing and communication functionalities. Specifically, we design transmit precoder to obtain 1-bit sensing waveforms having a desired radiation pattern. The RIS phase shifts are then designed to modulate the 1-bit sensing waveform to transmit M-ary phase shift keying symbols to users. T…
Joint Precoding and Phase-Shift Optimization for Beyond-Diagonal RIS-Aided ISAC System
School of Information Science and Engineering, Shandong University（山东大学信息科学与工程学院）；National Mobile Communications Research Laboratory, Southeast University（东南大学移动通信国家重点实验室）
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）
In this paper, we propose a novel integrated sensing and communication (ISAC) transmission framework based on the spatially-spread orthogonal time frequency space (SS-OTFS) modulation by considering the fact that communication channel strengths cannot be directly obtained from radar sensing. We first propose the concept of SS-OTFS modulation, where the key novelty is the angular domain discretization enabled by the spatial-spreading/de-spreading. This discretization gives rise to simple and insightful effective models for both radar sensing and communication, which result in simplified designs…
Environment-Aware Near-Field Channel Estimation Leveraging CKM and ISAC
The Chinese University of Hong Kong (Shenzhen)（香港中文大学（深圳））；Shenzhen Future Network of Intelligence Institute（深圳未来智能网络研究院）；National University of Singapore（新加坡国立大学）
Sensing Mutual Information for Communication Signal with Deterministic Pilots and Random Data Payloads
School of Cyber Science and Engineering, Southeast University（东南大学网络空间安全学院）；School of Information Science and Engineering, Southeast University（东南大学信息科学与工程学院）；School of Electrical, Computer, and Telecommunications Engineering, University of Wollongong（伍伦贡大学电气、计算机和电信工程学院）；Division of Integrative Systems and Design and the Department of Electronic and Computer Engineering, the Hong Kong University of Science and Technology（香港科技大学集成系统与设计分部及电子与计算机工程系）
Weighted Sum Rate Optimization for Movable Antenna Enabled Near-Field ISAC
Institute of Communications Engineering, National Sun Yat-sen University（国立中山大学通信工程研究所）；School of Electrical and Electronic Engineering, University College Dublin（都柏林大学电气与电子工程学院）
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）
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）
