Sparse Array Design for Dual-Function Radar-Communications System

The problem of sparse array design for dual-function radar-communications is investigated. Our goal is to design a sparse array which can simultaneously shape desired beam responses and serve multiple downlink users with the required signal-to-interference-plus-noise ratio levels. Besides, we also take into account the limitation of the radiated power by each antenna. The problem is formulated as a quadratically constrained quadratic program with a joint-sparsity-promoting regularization, which is NP-hard. The resulting problem is solved by the consensus alternating direction method of multipliers, which enjoys parallel implementation. Numerical simulations exhibit the effectiveness and superiority of the proposed method which leads to a more power-efficient solution.Comment: Accepted by IEEE Communications Letter

Double-Phase-Shifter based Hybrid Beamforming for mmWave DFRC in the Presence of Extended Target and Clutters

In millimeter-wave (mmWave) dual-function radar-communication (DFRC) systems, hybrid beamforming (HBF) is recognized as a promising technique utilizing a limited number of radio frequency chains. In this work, in the presence of extended target and clutters, a HBF design based on the subarray connection architecture is proposed for a multiple-input multiple-output (MIMO) DFRC system. In this HBF, the double-phase-shifter (DPS) structure is embedded to further increase the design flexibility. We derive the communication spectral efficiency (SE) and radar signal-to-interference-plus-noise-ratio (SINR) with respect to the transmit HBF and radar receiver, and formulate the HBF design problem as the SE maximization subjecting to the radar SINR and power constraints. To solve the formulated nonconvex problem, the joinT Hybrid bRamforming and Radar rEceiver OptimizatioN (THEREON) is proposed, in which the radar receiver is optimized via the generalized eigenvalue decomposition, and the transmit HBF is updated with low complexity in a parallel manner using the consensus alternating direction method of multipliers (consensus-ADMM). Furthermore, we extend the proposed method to the multi-user multiple-input single-output (MU-MISO) scenario. Numerical simulations demonstrate the efficacy of the proposed algorithm and show that the solution provides a good trade-off between number of phase shifters and performance gain of the DPS HBF

Multi-IRS-Aided Doppler-Tolerant Wideband DFRC System

peer reviewedIntelligent reflecting surface (IRS) is recognized as an enabler of future dual-function radar-communications (DFRC) by improving spectral efficiency, coverage, parameter estimation, and interference suppression. Prior studies on IRS-aided DFRC focus either on narrowband processing, single-IRS deployment, static targets, non-clutter scenario, or on the under-utilized line-of-sight (LoS) and non-line-of-sight (NLoS) paths. In this paper, we address the aforementioned shortcomings by optimizing a wideband DFRC system comprising multiple IRSs and a dual-function base station that jointly processes the LoS and NLoS wideband multi-carrier signals to improve both the communications SINR and the radar SINR in the presence of a moving target and clutter. We formulate the transmit, receive and IRS beamformer design as the maximization of the worst-case radar signal-to-interference-plus-noise ratio (SINR) subject to transmit power and communications SINR. We tackle this nonconvex problem under the alternating optimization framework, where the subproblems are solved by a combination of Dinkelbach algorithm, consensus alternating direction method of multipliers, and Riemannian steepest decent. Our numerical experiments show that the proposed multi-IRS-aided wideband DFRC provides over 4 dB radar SINR and 31.7% improvement in target detection over a single-IRS system

Simultaneous Active-Passive Beamformer Design in IRS-Enabled Multi-Carrier DFRC System

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IRS-Aided Wideband Dual-Function Radar-Communications with Quantized Phase-Shifts

peer reviewedIntelligent reflecting surfaces (IRS) are increasingly considered as an emerging technology to assist wireless communications and target sensing. In this paper, we consider the quantized IRS-aided wideband dual-function radar-communications system with multi-carrier signaling. Specifically, the radar receive filter, frequency-dependent transmit beamforming and discrete phase-shifts are jointly designed to maximize the average signal-to-interference-plus-noise ratio (SINR) for radar while guaranteeing the communication SINR among all users. The resulting optimization problem has a fractional quartic objective function with difference of convex and discrete phase constraints and is, therefore, highly non-convex. Thus, we solve this problem via the alternating maximization framework, in which the alternating direction method of multipliers and Dinkelbach's algorithm are integrated to tackle the related subproblems. Numerical results demonstrate that the proposed method, even with the low-resolution IRS, achieves better sensing performance compared with non-IRS system

Multiple IRS-Assisted Wideband Dual-Function Radar-Communication

peer reviewedWe propose a novel dual-function radar-communications (DFRC) system that relies on multiple intelligent reflecting surfaces (IRSs) to enhance detection of non-line-of-sight (NLoS) targets. In particular, we consider a wideband OFDM transmit signal for which we jointly design the frequency-dependent beamforming and phase shifts to maximize the average SINR of radar and the minimal communication SINR among all users. We solve the resulting highly nonconvex problem comprising maximin objective function with a difference of convex (DC) constraint through an alternating maximization (AM) framework of alternating direction method of multipliers (ADMM) and Dinkelbach's method. Numerical experiments demonstrate that the proposed method with multiple IRS can achieve 3.3 dB radar SINR enhancement and 0.9 dB minimal communication SINR improvement compared with single IRS scenario

RIS-Aided Wideband DFRC with Reconfigurable Holographic Surface

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Next-Generation IoT Networks: Integrated Sensing Communication and Computation

peer reviewedTo enable the exponential expansion of Internet of Things (IoT) applications, IoT devices must gather and transmit massive amounts of data to the server for further processing. By employing the same signals for both radar sensing and data transmission, the integrated sensing and communication (ISAC) approach provides simultaneous data gathering and delivery in the physical layer. Over-the-air computation (AirComp), which leverages the analog-wave addition property in multi-access channels, is a communication method that also supports function computation. In order to leverage the individual benefits of ISAC and AirComp, this work focuses on Integrated Sensing Communication and Computation (ISCCO) framework for the IoT network. Since the IoT sensors are small size low cost devices and each is equipped with single antenna, and hence to make the processing of received echo simple this work assume that the waveform transmitted by each sensor is orthogonal to each other. Furthermore, joint optimal power allocation for each sensor in the IoT network and the combining vector at the EC is designed such that the signal-to-noise (SNR) ratio at the EC is maximized. However, the design challenge lies in the non-convex joint optimal power allocation for each IoT device and the combining vector at the server. To address this, an iterative algorithm is proposed which provides closed-form solution for each quantity in each iteration. Results show that the proposed optimal power allocation and orthogonal waveform design scheme outperforms the equal power allocation-based design.9. Industry, innovation and infrastructur

Joint waveform and precoding design for coexistence of MIMO radar and MU-MISO communication

peer reviewedThe joint design problem for the coexistence of multiple-input multiple-output (MIMO) radar and multi-user multiple-input-single-output (MU-MISO) communication is investigated. Different from the conventional design schemes, which require defining the primary function, we consider designing the transmit waveform, precoding matrix and receive filter to maximize the radar SINR and the minimal SINR of communication users, simultaneously. By doing so, the promising overall performance for both sensing and communication is achieved without requiring parameter tuning for the threshold of communication or radar. However, the resulting optimization problem which contains the maximin objective function and the unit sphere constraint, is highly nonconvex and hence difficult to attain the optimal solution directly. Towards this end, the epigraph-form reformulation is first adopted, and then an alternating maximisation (AM) method is devised, in which the Dinkelbach’s algorithm is used to tackle the nonconvex fractional-programing subproblem. Simulation results indicate that the proposed method can achieve improved performance compared with the benchmarks