Signal Processing for Joint Communication and Radar Sensing Techniques in Autonomous Vehicular Networks

University of Technology Sydney. Faculty of Engineering and Information Technology.Joint communication and radar (radio) sensing (JCAS, also known as Radar-Communications) technology is promising for autonomous vehicular networks, for its appealing capability of realizing communication and radar sensing functions in an integrated system. Millimeter wave (mmWave) band has great potential forJCAS, and such mmWave systems often require the use of steerable array radiation beams. Therefore, beamforming (BF) is becoming a demanding feature in JCAS. Multibeam technology enables the use of two or more subbeams in JCAS systems,to meet different requirements of beamwidth and pointing directions. Generating and optimizing multibeam subject to the requirements is critical and challenging, particularly for systems using analog arrays. In this thesis, we investigate the BF techniques for JCAS, addressing the following two issues: 1. The multibeam generation and optimization for JCAS, considering both communication and sensing performance; 2. BF generation in the presence of hardware imperfections in mmWave JCASsystems, particularly those associated with quantized phase shifters, and the radiation characteristics of antenna arrays. Regarding the first issue, we mainly study two classes of multibeam generation methods: 1) the optimal combination of two pre-generated subbeams, and their BF vectors, using a combining phase coefficient; 2) global optimization methods which directly find solutions for a single BF vector. For the optimal combination problems, we firstly study the communication-focused optimization in two typical scenarios. We also develop constrained optimization problems, considering both the communication and sensing performances. Closed-form solutions for the optimal combination coefficient are provided in these works. We also formulate several global optimization problems and managed to provide near-optimal solutions to the original intractable complex NP-hard optimization problems, using semidefinite relaxation (SDR) techniques. Towards the second issue, we firstly study the quantization of the BF weight vector with the use of phase shifters. We focus on the two-phase-shifter array, where two phase shifters are used to represent each BF weight. We propose novel joint quantization methods by combining the codebooks of the two phase shifters. Analytically, the mean squared quantization error (MSQE) is derived for various quantization methods. We also propose BF methods by embedding the active pattern of antennas in the robust BF algorithms: 1) the diagonal loading and 2) the worst-case performance optimization algorithms. With the use of a more accurate array model, these methods can significantly reduce performance degradation caused by inconsistency between hypothesized ideal array models and practical ones

An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing

Joint communication and radar sensing (JCR) represents an emerging research field aiming to integrate the above two functionalities into a single system, by sharing the majority of hardware, signal processing modules and, in a typical case, the transmitted signal. The close cooperation of the communication and sensing functions can enable significant improvement of spectrum efficiency, reduction of device size, cost and power consumption, and improvement of performance of both functions. Advanced signal processing techniques are critical for making the integration efficient, from transmission signal design to receiver processing. This paper provides a comprehensive overview of the state-of-the-art on JCR systems from the signal processing perspective. A balanced coverage on both transmitter and receiver is provided for three types of JCR systems, namely, communication-centric, radar-centric, and joint design and optimization

Beamformer Design and Optimization for Joint Communication and Full-Duplex Sensing at mm-Waves

In this article, we study the joint communication and sensing (JCAS) paradigm in the context of millimeter-wave (mm-wave) mobile communication networks. We specifically address the JCAS challenges stemming from the full-duplex operation in monostatic orthogonal frequency-division multiplexing (OFDM) radars and from the co-existence of multiple simultaneous beams for communications and sensing purposes. To this end, we first formulate and solve beamforming optimization problems for hybrid beamforming based multiuser multiple-input and multiple-output JCAS systems. The cost function to be maximized is the beamformed power at the sensing direction while constraining the beamformed power at the communications directions, suppressing interuser interference and cancelling full-duplexing related self-interference (SI). We then also propose new transmitter and receiver beamforming solutions for purely analog beamforming based JCAS systems that maximize the beamforming gain at the sensing direction while controlling the beamformed power at the communications direction(s), cancelling the SI as well as eliminating the potential reflection from the communication direction and optimizing the combined radar pattern (CRP). Both closed-form and numerical optimization based formulations are provided. We analyze and evaluate the performance through extensive numerical experiments, and show that substantial gains and benefits in terms of radar transmit gain, CRP, and SI suppression can be achieved with the proposed beamforming methods.publishedVersionPeer reviewe

Holographic MIMO Communications: Theoretical Foundations, Enabling Technologies, and Future Directions

Future wireless systems are envisioned to create an endogenously holography-capable, intelligent, and programmable radio propagation environment, that will offer unprecedented capabilities for high spectral and energy efficiency, low latency, and massive connectivity. A potential and promising technology for supporting the expected extreme requirements of the sixth-generation (6G) communication systems is the concept of the holographic multiple-input multiple-output (HMIMO), which will actualize holographic radios with reasonable power consumption and fabrication cost. The HMIMO is facilitated by ultra-thin, extremely large, and nearly continuous surfaces that incorporate reconfigurable and sub-wavelength-spaced antennas and/or metamaterials. Such surfaces comprising dense electromagnetic (EM) excited elements are capable of recording and manipulating impinging fields with utmost flexibility and precision, as well as with reduced cost and power consumption, thereby shaping arbitrary-intended EM waves with high energy efficiency. The powerful EM processing capability of HMIMO opens up the possibility of wireless communications of holographic imaging level, paving the way for signal processing techniques realized in the EM-domain, possibly in conjunction with their digital-domain counterparts. However, in spite of the significant potential, the studies on HMIMO communications are still at an initial stage, its fundamental limits remain to be unveiled, and a certain number of critical technical challenges need to be addressed. In this survey, we present a comprehensive overview of the latest advances in the HMIMO communications paradigm, with a special focus on their physical aspects, their theoretical foundations, as well as the enabling technologies for HMIMO systems. We also compare the HMIMO with existing multi-antenna technologies, especially the massive MIMO, present various...Comment: double column, 58 page

Time-Frequency-Space Transmit Design and Signal Processing with Dynamic Subarray for Terahertz Integrated Sensing and Communication

Terahertz (THz) integrated sensing and communication (ISAC) enables simultaneous data transmission with Terabit-per-second (Tbps) rate and millimeter-level accurate sensing. To realize such a blueprint, ultra-massive antenna arrays with directional beamforming are used to compensate for severe path loss in the THz band. In this paper, the time-frequency-space transmit design is investigated for THz ISAC to generate time-varying scanning sensing beams and stable communication beams. Specifically, with the dynamic array-of-subarray (DAoSA) hybrid beamforming architecture and multi-carrier modulation, two ISAC hybrid precoding algorithms are proposed, namely, a vectorization (VEC) based algorithm that outperforms existing ISAC hybrid precoding methods and a low-complexity sensing codebook assisted (SCA) approach. Meanwhile, coupled with the transmit design, parameter estimation algorithms are proposed to realize high-accuracy sensing, including a wideband DAoSA MUSIC (W-DAoSA-MUSIC) method for angle estimation and a sum-DFT-GSS (S-DFT-GSS) approach for range and velocity estimation. Numerical results indicate that the proposed algorithms can realize centi-degree-level angle estimation accuracy and millimeter-level range estimation accuracy, which are one or two orders of magnitudes better than the methods in the millimeter-wave band. In addition, to overcome the cyclic prefix limitation and Doppler effects in the THz band, an inter-symbol interference- and inter-carrier interference-tackled sensing algorithm is developed to refine sensing capabilities for THz ISAC

Performance of RIS-Aided Nearfield Localization under Beams Approximation from Real Hardware Characterization

The technology of reconfigurable intelligent surfaces (RIS) has been showing promising potential in a variety of applications relying on Beyond-5G networks. Reconfigurable intelligent surface (RIS) can indeed provide fine channel flexibility to improve communication quality of service (QoS) or restore localization capabilities in challenging operating conditions, while conventional approaches fail (e.g., due to insufficient infrastructure, severe radio obstructions). In this paper, we tackle a general low-complexity approach for optimizing the precoders that control such reflective surfaces under hardware constraints. More specifically, it allows the approximation of any desired beam pattern using a pre-characterized look-up table of feasible complex reflection coefficients for each RIS element. The proposed method is first evaluated in terms of beam fidelity for several examples of RIS hardware prototypes. Then, by means of a theoretical bounds analysis, we examine the impact of RIS beams approximation on the performance of near-field downlink positioning in non-line-of-sight conditions, while considering several RIS phase profiles (incl. directional, random and localization-optimal designs). Simulation results in a canonical scenario illustrate how the introduced RIS profile optimization scheme can reliably produce the desired RIS beams under realistic hardware limitations. They also highlight its sensitivity to both the underlying hardware characteristics and the required beam kinds in relation to the specificity of RIS-aided localization applications.Comment: 27 pages, 8 figures, journa

Joint Communication and Sensing Design for Beyond 5G System

Joint communication and sensing (JCAS) is an emerging research topic aiming to integrate radio communications and radar systems in time and frequency domains along with the spatial domain. Integration in the spatial domain relies on a suitable beamforming technique for acquiring desired detection performance levels for both operations. Beamforming methods in the context of JCAS systems, with an emphasis on convex optimization, are studied in this thesis. A previously established work on beamformer design for optimum antenna selection is reviewed and duplicated to establish the groundwork for the main research. The novel beamforming algorithm proposed in this work maximizes the detection performance for the radar function in a JCAS system while maintaining the communication performance at an acceptable level. This is accomplished in the presence of clutter and with no assumption of a direct path between the transmitter and the communication user. A mathematical groundwork is presented for acquiring a valid convex optimization problem to represent the beamforming objective and constraints, along with using rank one decomposition to convert the result into a beamforming weight vector usable in practical application. The tests performed on a simulation environment showed that performance tradeoffs between radar and communication functions are observable on acquired results, in addition to assurance about the validity of assumptions made during problem definition