Velocity ambiguity is a challenging problem that exists in automotive radar. While velocity disambiguation is typically achieved through signal processing and the transmission of multiple frames with different signaling, we propose a multitarget tracker that can resolve velocity ambiguity by transmitting frames with a single signaling and utilizing tracking information such as filtering and data association. Furthermore, we present a modified version of the proposed tracker for multiple-input multiple-output (MIMO) radars with time-division multiplexing (TDM), where accurate angle estimation must be performed after Doppler disambiguation. Our simulations demonstrate the effectiveness of the proposed trackers in simultaneously tracking and disambiguating velocity in automotive radar scenarios.

In this paper, we optimize a Wireless Information and Power Transfer (WIPT) system including multiple pairs of users, where transmitters employ a single-antenna to transmit their information and power to their receivers with the help of one multiple-antenna Amplify-and-Forward (AF) relay or an active Intelligent Reflecting Surface (IRS). We propose a joint Time Switching (TS) scheme in which transmitters, receivers, and the relay/IRS are either in their energy or information transmission/reception modes. The transmitted multi-carrier unmodulated and modulated waveforms are used for Energy Harvesting (EH) and Information Decoding (ID) modes, respectively. In order to design an optimal fair system, we maximize the minimum rate of all pairs for both relay and IRS systems through a unified framework. This framework allows us to simultaneously design energy waveforms, find optimal relay/IRS amplification/reflection matrices, allocate powers for information waveforms, and allocate time durations for various phases. This problem turns out to be non-convex. Thus, we propose an iterative algorithm by using the Minorization-Maximization (MM) technique, which efficiently converges to the optimized solution, i.e., stationary point of the problem (under mild conditions). Numerical examples show that the proposed method improves the performance of the multi-pair WIPT relay/IRS system under various setups.

In this paper, we consider an integrated sensing and communication (ISAC) system with wireless power transfer (WPT) where an unmanned aerial vehicle (UAV)-based radar serves a group of energy-limited communication users in addition to its sensing functionality. In this architecture, the radar senses the environment in phase 1 (namely sensing phase) and mean-while, the communications users (nodes) harvest and store the energy from the radar transmit signal. The stored energy is then used for information transmission from the nodes to UAV in phase 2, i.e., uplink phase. Performance of the radar system depends on the transmit signal as well as the receive filter; the energy of the transmit signal also affects the communication network because it serves as the source of uplink powers. Therefore, we cast a multi-objective design problem addressing performance of both radar and communication systems via optimizing radar transmit waveform, radar receive filter, time scheduling and uplink powers. We further take into account optimization of UAV trajectory for covering a given coverage area. The design problem is non-convex and hence, we devise a method based on alternating optimization followed by concepts of fractional programming as well as tricky majorization-minimization technique to tackle it. Numerical examples illustrate the effectiveness of the pro-posed method for performance improvement of the considered ISAC system.

This paper is concerned with the energy efficiency maximization problem in multiple-input multiple-output interference channels. In the first part of this paper, we design the transmit beamforming matrices based on three approaches. In the first approach, each user tries to maximize their own energy efficiency, resulting in what we call the selfish method. The maximization problem corresponding to the selfish method can be implemented in a distributed manner with a semi-closed-form solution. The second approach aims to maximize the weighted sum-energy efficiency; we refer to it as the unselfish method. The proposed unselfish method has the following advantages. 1) It is easily implementable as the problem can be divided into several sub-problems and solved in a distributed manner. 2) It results in a quadratically constrained quadratic program with a semi-closed-form solution. Also, we consider fairness with the minimum-energy efficiency maximization problem, an approach that results in what we call the worst-case method. In the second part, general energy efficiency maximization in the presence of norm-bounded channel uncertainty is investigated which leads to a semi-definite program; the resulting method is called the robust method. Finally, the effect of the system parameters is evaluated through simulations.

This paper studies a general multi-user wireless powered interference channel (IFC) under the harvest-then-transmit protocol, where the communication in channel coherence time consists of two phases, namely wireless energy transfer (WET) and wireless information transfer (WIT). In the first phase, all energy transmitters (ETs) transmit energy signals to information transmitters (ITs) via the collaborative waveform design, while in the second phase, each IT transmits an information signal to its intended ET using the harvested energy in the previous phase. The aim is to jointly design the WET-WIT time allocation, the (deterministic) transmit signal at the first phase, and the transmit power of ITs in the second phase to optimize the network throughput. The design problems are non-convex and hence difficult to solve globally. To deal with them, we propose efficient iterative algorithms based on alternating projections; then, the majorization-minimization technique is used to tackle the non-convex sub-problems in each iteration. We also extend the devised design methodology by considering imperfect channel state information and non-linearity in energy harvesting circuit. The proposed algorithms are locally convergent and can provide high-quality suboptimal solutions to the design problems. The simulation results show the effectiveness of the proposed algorithms under various setups.

We investigate a partially blind channel estimation and symbol detection in an amplify-and-forward two way relay scheme. We derive generalized likelihood ratio test detectors for reciprocal and non-reciprocal channels, whose computational complexity (CC) grow exponentially with the block length. Therefore, we propose a convergent iterative method for joint channel estimation and symbol detection with CC proportional to the block length. We also address the convergence proof. We further propose the simple blind and partially-blind approaches based on least squares (LS) and weighted LS estimation, respectively, for operation at low SNRs and analyze their mean square errors (MSE). Our simulations reveal the effectiveness of the proposed method compared with its counterparts.

This paper proposes a compressive pulse-Doppler radar that works through one-bit quantization of the received noisy signal. The one-bit quantization is performed by comparing the signal with a time-varying reference level. Considering the sparsity of the targets in the range-Doppler domain, the problem is dealt with by a sparse recovery method. The proposed method leads to an optimization problem that can be tackled by a convex approximation. Numerical examples show that the proposed method has a promising performance in the detection/estimation of the target parameters. Moreover, it is seen that in low signal to noise ratio, increasing the sampling rate at the receiver side is a compensating factor that effectively improves the performance.

In this paper, we propose a new approach to the design of training sequences that can be used for an accurate estimation of multi-input multi-output channels. The proposed method is particularly instrumental in training sequence designs that deal with three key challenges: 1) arbitrary channel and noise statistics that do not follow specific models, 2) limitations on the properties of the transmit signals, including total power, per-antenna power, having a constant-modulus, discrete-phase, or low peak-to-average-power ratio, and 3) signal design for large-scale or massive antenna arrays. Several numerical examples are provided to examine the proposed method.

We consider the problem of sum-rate maximization in massive MIMO two-way relay networks with multiple (communication) operators employing the amplify-and-forward (AF) protocol. The aim is to design the relay amplification matrix (i.e., the relay beamformer) to maximize the achievable communication sum-rate through the relay. The design problem for the case of single-antenna users can be cast as a non-convex optimization problem, which in general, belongs to a class of NP-hard problems. We devise a method based on the minorization-maximization technique to obtain quality solutions to the problem. Each iteration of the proposed method consists of solving a strictly convex unconstrained quadratic program; this task can be done quite efficiently such that the suggested algorithm can handle the beamformer design for relays with up to ∼ 70 antennas within a few minutes on an ordinary PC. Such a performance lays the ground for the proposed method to be employed in massive MIMO scenarios.

We consider the problem of sum-rate maximization in multiple-input multiple-output (MIMO) amplify-and-forward relay networks with multi-operator. The aim is to design the MIMO relay amplification matrix (i.e., the relay beamformer) to maximize the achievable communication sum rate through the relay. The design problem for the case of single-antenna users can be cast as a non-convex optimization problem, which, in general, belongs to a class of NP-hard problems. We devise a method based on the minorization–maximization technique to obtain quality solutions to the problem. Each iteration of the proposed method consists of solving a strictly convex unconstrained quadratic program. This task can be done quite efficiently, such that the suggested algorithm can handle the beamformer design for relays with up to$\sim 70$antennas within a few minutes on an ordinary personal computer. Such a performance lays the ground for the proposed method to be employed in medium-scale (or lower regime massive) MIMO scenarios.

In this paper, we consider the problem of transmit code design to optimize the detection probability of an extended target embedded in Gaussian signal-dependent interference. We model the target with a priori known target impulse response (TIR) structure along with an unknown reflection factor. As is known, the performance of the generalized likelihood ratio test (GLRT) detector, for the case at hand, monotonically increases with the signal-to-interference-plus-noise ratio (SINR). Hence, we deal with the code design problem via maximizing the SINR. We also enforce a peak-to-average power ratio (PAR) constraint on the sought code. We devise a cyclic method to tackle the highly non-convex design problem. Numerical results highlight the effectiveness of the proposed method to improve the detection performance of the system.

In this paper, we study the problem of unimodular code design to improve the detection performance of statistical multiple-input multiple-output (MIMO) radar systems. To this end, we consider a system transmitting arbitrary unimodular signals and a discrete-time formulation of the problem. Due to the complicated form of the performance metric of the optimal detector, we resort to the Bhattacharyya distance for code design. We devise a novel method based on the majorization of matrix functions to obtain solutions to the constrained design problem. Simulation results show the effectiveness of the proposed method.

In this paper, we study the joint design of Doppler robust transmit sequence and receive filter to improve the performance of an active sensing system dealing with signal-dependent interference. The signal-to-interference-plus-noise ratio (SINR) of the filter output is considered as the performance measure of the system. The design problem is cast as a max-min optimization problem to robustify the system SINR with respect to the unknown Doppler shifts of the targets. To tackle the design problem, we devise a novel method to obtain optimized pairs of transmit sequence and receive filter sharing the desired robustness property.

In this paper, we study the problem of approaching peak periodic or aperiodic correlation bounds for complex-valued sets of sequences. In particular, novel algorithms based on alternating projections are devised to approach a given peak periodic or aperiodic correlation bound. Several numerical examples are presented to assess the tightness of the known correlation bounds as well as to illustrate the effectiveness of the proposed methods for meeting these bounds.

Orthogonal frequency division multiplexing (OFDM) is a mature and one of the most popular multicarrier modulation (MCM) techniques. Also, it is the main candidate for physical layer of cognitive radio (CR) networks. CR is a new method to satisfy ubiquitous demand for wireless services while there is no enough unlicensed spectrum. However, the most important shortcoming of OFDM-based CR systems is the high level of out of band (OOB) components that originate from simple fast Fourier transform (FFT)-based implementation. In this study, the authors propose a novel method to reduce side-lobes of OFDM spectrum. In this method proper carrier-by-carrier partial response signaling is used on the modulated symbols across the time. This method will allow for using other techniques for OOB radiation or peak-to-average power ratio (PAPR) reduction, while does not require high complexity at the transmitter, i.e. just the receiver should have either maximum likelihood sequence detector (MLSD) in case of no pre-coding or a simple slicer in case of pre-coding. Moreover, it will not affect the PAPR but will increase word error rate (WER). Simulation results show that about 7 dB reduction in OOB components can be expected by this method.