Future wireless communication systems are expected to explore spectral bands typically used by radar systems, in order to overcome spectrum congestion of traditional communication bands. Since in many applications radar and communication share the same platform, spectrum sharing can be facilitated by joint design as a dual-function radar-communications system. In this paper, we propose a joint transmit beamforming model for a dual-function multiple-input-multiple-output (MIMO) radar and multiuser MIMO communication transmitter. The proposed dual-function system transmits the weighted sum of independent radar waveforms and communication symbols, forming multiple beams towards the radar targets and the communication receivers, respectively. The design of the weighting coefficients is formulated as an optimization problem whose objective is the performance of the MIMO radar transmit beamforming, while guaranteeing that the signal-to-interference-plus-noise ratio (SINR) at each communication user is higher than a given threshold. Despite the non-convexity of the proposed optimization problem, we prove that it can be relaxed into a convex one, where the relaxation is tight. We then propose a reduced complexity design based on zero-forcing the inter-user interference and radar interference. Unlike previous works, which focused on the transmission of communication symbols to synthesize a radar transmit beam pattern, our method provides more degrees of freedom for MIMO radar and is thus able to obtain improved radar performance, as demonstrated in our simulation study. Furthermore, the proposed dual-function scheme approaches the radar performance of the radar-only scheme, i.e., without spectrum sharing, under reasonable communication quality constraints.

Joint Transmit Beamforming for Multiuser MIMO Communications and MIMO Radar

Massive multiple-input multiple-output (MIMO) is a key technology to meet the user demands in performance and quality of services (QoS) for next generation communication systems. Due to a large number of antennas and radio frequency (RF) chains, complexity of the symbol detectors increased rapidly in a massive MIMO uplink receiver. Thus, the research to find the perfect massive MIMO detection algorithm with optimal performance and low complexity has gained a lot of attention during the past decade. A plethora of massive MIMO detection algorithms has been proposed in the literature. The aim of this paper is to provide insights on such algorithms to a generalist of wireless communications. We garner the massive MIMO detection algorithms and classify them so that a reader can find a distinction between different algorithms from a wider range of solutions. We present optimal and near-optimal detection principles specifically designed for the massive MIMO system such as detectors based on a local search, belief propagation and box detection. In addition, we cover detectors based on approximate inversion, which has gained popularity among the VLSI signal processing community due to their deterministic dataflow and low complexity. We also briefly explore several nonlinear small-scale MIMO (2-4 antenna receivers) detectors and their applicability in the massive MIMO context. In addition, we present recent advances of detection algorithms which are mostly based on machine learning or sparsity based algorithms. In each section, we also mention the related implementations of the detectors. A discussion of the pros and cons of each detector is provided.

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Massive MIMO Detection Techniques: A Survey

Mobile network is evolving from a communication-only network towards the one with joint communication and radio/radar sensing (JCAS) capabilities, that we call perceptive mobile network (PMN). Radio sensing here refers to information retrieval from received mobile signals for objects of interest in the environment surrounding the radio transceivers. In this paper, we provide a comprehensive survey for systems and technologies that enable JCAS in PMN, with a focus on works in the last ten years. Starting with reviewing the work on coexisting communication and radar systems, we highlight their limits on addressing the interference problem, and then introduce the JCAS technology. We then set up JCAS in the mobile network context, and envisage its potential applications. We continue to provide a brief review for three types of JCAS systems, with particular attention to their differences on the design philosophy. We then introduce a framework of PMN, including the system platform and infrastructure, three types of sensing operations, and signals usable for sensing, and discuss required system modifications to enable sensing on current communication-only infrastructure. Within the context of PMN, we review stimulating research problems and potential solutions, organized under eight topics: mutual information, waveform optimization, antenna array design, clutter suppression, sensing parameter estimation, pattern analysis, networked sensing under cellular topology, and sensing-assisted secure communication. This paper provides a comprehensive picture for the motivation, methodology, challenges, and research opportunities of realizing PMN. The PMN is expected to provide a ubiquitous radio sensing platform and enable a vast number of novel smart applications.

Enabling Joint Communication and Radio Sensing in Mobile Networks -- A Survey

Joint radar and communication (JRC) technology has become important for civil and military applications for decades. This paper introduces the concepts, characteristics and advantages of JRC technology, presenting the typical applications that have benefited from JRC technology currently and in the future. This paper explores the state-of-the-art of JRC in the levels of coexistence, cooperation, co-design and collaboration. Compared to previous surveys, this paper reviews the entire trends that drive the development of radar sensing and wireless communication using JRC. Specifically, we explore an open research issue on radar and communication operating with mutual benefits based on collaboration, which represents the fourth stage of JRC evolution. This paper provides useful perspectives for future researches of JRC technology.

Joint radar and communication: A survey

Joint radar and communication (JRC) has recently attracted substantial attention. The first reason is that JRC allows individual radar and communication systems to share spectrum bands and thus improves the spectrum utilization. The second reason is that JRC enables a single hardware platform, e.g., an autonomous vehicle or a UAV, to simultaneously perform the communication function and the radar function. As a result, JRC is able to improve the efficiency of resources, i.e., spectrum and energy, reduce the system size, and minimize the system cost. However, there are several challenges to be solved for the JRC design. In particular, sharing the spectrum imposes the interference caused by the systems, and sharing the hardware platform and energy resource complicates the design of the JRC transmitter and compromises the performance of each function. To address the challenges, several resource management approaches have been recently proposed, and this paper presents a comprehensive literature review on resource management for JRC. First, we give fundamental concepts of JRC, important performance metrics used in JRC systems, and applications of the JRC systems. Then, we review and analyze resource management approaches, i.e., spectrum sharing, power allocation, and interference management, for JRC. In addition, we present security issues to JRC and provide a discussion of countermeasures to the security issues. Finally, we highlight important challenges in the JRC design and discuss future research directions related to JRC.

Radio Resource Management in Joint Radar and Communication: A Comprehensive Survey

The joint radar-communication system integrates the function of detection and data transmission to reduce interference and improve the overall spectrum efficiency, as well as to reduce total volume of devices in vehicles, which is widely used in the intelligent transportation systems. Among these joint systems, a MIMO radar based system has significant advantage for multi users with orthogonal waveforms transmitted by each antenna. In order to realize high speed transmission, a quasi-orthogonal multi-carrier LFM-CPM waveform is proposed for the joint system. This waveform preserves the characteristics of LFM with constant envelope and continuous phase, so that the distortion caused by the nonlinearity of the high power amplifier and the reduction of effective working distance can be avoided. The spectral efficiency of the proposed waveform is much higher than the 1-bit multi-carrier LFM waveform and simulation of bit error rate (BER) performance is close to that of single-carrier LFM-CPM with no interference. The simulation of ambiguity function shows that the random communication symbols has little influence on the radar subsystem. In a word, the shared waveform based on multi-carrier LFM-CPM and MIMO radar can meet the need of the detection and multi-user transmission at the same time, and is suitable for the intelligent transportation systems.

Waveform design for joint radar-communication system with multi-user based on MIMO radar

The integration of radar and communication has attracted general interest with its advantage of equipment miniaturizing and high efficiency of spectrum, especially in intelligent transportation systems because of the need for transmitting and detecting simultaneously and the lack of room for various devices. Among various integration schemes, the integrated waveform which realizes transmitting and detection at the same time is a real integration with high efficiency and no interference. In this paper, we proposed a modified three-section integrated waveform based on linear frequency modulation and continuous phase modulation (LFM-CPM). Short Time Fourier Transform (STFT) is used for time-frequency analysis and the modification of the mapping codebook of the communication symbols restrains the spectrum of the integrated waveform within the original bandwidth of the radar system. Simulation results show that the modified waveform holds good bit error rate (BER) performance even when there is strong interference beside the original bandwidth of the radar system, while the waveform without modification can hardly complete the transmission with high BER.

A Modified Waveform Design for Radar-Communication Integration Based on LFM-CPM

An integrated radar and communication system can cooperatively form a radar-communication network with significantly enhanced efficiency and considerably less occupied hardware resources. Such a system exhibits great advantages compared with traditional individual radar and communication modes. Numerous papers have proposed achieving the integrated functions based on phased array radar, whereas the channel modeling and channel estimation problems concerning communications are seldom discussed in the literature. In this paper, we propose a ray-cluster-based spatial channel model and a sounding channel estimation scheme realized on the existing hardware of phased array radar. Considering the correlation, we model the channel by comparing the difference between adjacent antennas, and we present the response vector of the antenna array. We analyze the number of beams that are needed to cover the space, and we present the sequence of directional beamforming vectors when sounding the channel. Redundant dictionary matrices are utilized to present the channel as a sparse signal recovery problem, in which the spatial sparsity is leveraged for performance enhancement. A sparsity adaptive matching pursuit (SAMP)-based compressed sensing tool is exploited for the sparse recovery problem and compared with the conventional least squares (LS) algorithm. The experimental results demonstrate that our proposed scheme can effectively solve the channel estimation problem in the integrated radar and communication system with reduced complexity, and it outperforms LS by 25% when considering mean square error (MSE) performance in general.

Phased Array Radar-Based Channel Modeling and Sparse Channel Estimation for an Integrated Radar and Communication System

The direct-to-home satellite digital video broadcasting has been fast developed in the past decades, and the continuous phase modulation (CPM) is an alternative modulation scheme with the advantages of constant envelope and high spectral efficiency for the band-limited channel and non-linear amplifiers of the satellite transponder. In this paper, CPM cascaded with irregular low density parity check (LDPC) code is studied. A practical system model with global interleaving is proposed for the optimization of degree distribution of the LDPC codes, and code word design is obtained with a modified progressive edge-growth algorithm. Simulation results combined with theoretical analysis clarify the effect of signal-to-noise ratios and two important CPM parameters (modulation index ${h}$ and correlation length ${L}$ ), providing guidance for system design. Simulation on bit error rate performance show the validity of the proposed algorithm. This paper systematically solves the optimal system design of cascade irregular LDPC-CPM and is of great significance for future satellite broadcasting.

Optimal Design of Cascade LDPC-CPM System Based on Bionic Swarm Optimization Algorithm

The joint radar-communication system is a good way to meet the intelligent transportation systems' need of detecting the cars and barriers around and exchanging information from each other at the same time. Among various schemes, the joint system with integrated waveform attracts general interest because the interference between the radar and communication subsystems will be fundamentally avoided. For all kinds of integrated waveforms, the spectrum must be limited within $B_0$, the original working band of the radar, in order to avoid the performance loss brought by the attenuation of the power amplifier (PA) and the interference from other devices out of band, which is inevitable in actual devices and environment. In this paper, the time-frequency characteristics of an integrated waveform based on Linear Frequency Modulation (LFM) and Continuous Phase Modulation (CPM) is studied in detail with the Short Time Fourier Transform (STFT). Based on the theoretical analysis, a modified three-section waveform with a limit of the mapping codebook of communication symbols is proposed. Simulation results show that the bandwidth of the modified waveform is limited within $B_0$ and the bit error rate (BER) performance with a band-limited PA and out-band interference is almost the same as the BER with ideal PA and no interference.

Ling Huang

Papers

Waveform design for joint radar-communication system with multi-user based on MIMO radar

A Modified Waveform Design for Radar-Communication Integration Based on LFM-CPM

Phased Array Radar-Based Channel Modeling and Sparse Channel Estimation for an Integrated Radar and Communication System

Optimal Design of Cascade LDPC-CPM System Based on Bionic Swarm Optimization Algorithm

Waveform Design for Joint Radar-Communication with Nonideal Power Amplifier and Outband Interference