Aboulnasr Hassanien

Bio: Aboulnasr Hassanien is an academic researcher from Wright State University. The author has contributed to research in topics: Radar & MIMO. The author has an hindex of 28, co-authored 79 publications receiving 3012 citations. Previous affiliations of Aboulnasr Hassanien include University of Alberta & McMaster University.

Dual-Function Radar-Communications: Information Embedding Using Sidelobe Control and Waveform Diversity

Abstract: We develop a new technique for a dual-function system with joint radar and communication platforms. Sidelobe control of the transmit beamforming in tandem with waveform diversity enables communication links using the same pulse radar spectrum. Multiple simultaneously transmitted orthogonal waveforms are used for embedding a sequence of LB bits during each radar pulse. Two weight vectors are designed to achieve two transmit spatial power distribution patterns, which have the same main radar beam, but differ in sidelobe levels towards the intended communication receivers. The receiver interpretation of the bit is based on its radiated beam. The proposed technique allows information delivery to single or multiple communication directions outside the mainlobe of the radar. It is shown that the communication process is inherently secure against intercept from directions other than the pre-assigned communication directions. The employed waveform diversity scheme supports a multiple-input multiple-output radar operation mode. The performance of the proposed technique is investigated in terms of the bit error rate.

Phased-MIMO Radar: A Tradeoff Between Phased-Array and MIMO Radars

Abstract: We propose a new technique for multiple-input multiple-output (MIMO) radar with colocated antennas which we call phased-MIMO radar. The new technique enjoys the advantages of the MIMO radar without sacrificing the main advantage of the phased-array radar which is the coherent processing gain at the transmitting side. The essence of the proposed technique is to partition the transmit array into a number of subarrays that are allowed to overlap. Then, each subarray is used to coherently transmit a waveform which is orthogonal to the waveforms transmitted by other subarrays. Coherent processing gain can be achieved by designing a weight vector for each subarray to form a beam towards a certain direction in space. Moreover, the subarrays are combined jointly to form a MIMO radar resulting in higher angular resolution capabilities. Substantial improvements offered by the proposed phased-MIMO radar technique as compared to the phased-array and MIMO radar techniques are demonstrated analytically and by simulations through analyzing the corresponding beam patterns and the achievable output signal-to-noise-plus-interference ratios. Both analytical and simulation results validate the effectiveness of the proposed phased-MIMO radar.

Signaling strategies for dual-function radar communications: an overview

Abstract: The last decade witnessed a growing demand on radio frequency that is driven by technological advances benefiting the end consumer but requiring new allocations of frequency bandwidths. Further, higher data rates for faster communications and wireless connections have called for an expanded share of existing frequency allocations. Concerns for spectrum congestion and frequency unavailability have spurred extensive research efforts on spectrum management and efficiency [1]-[4] within the same type of service and have led to cognitive radio [5] and cognitive radar [6]. On the other hand, devising schemes for coexistence among different services have eased the competition for spectrum resources, especially for radar and wireless communication systems [7]-[14]. Both systems have been recently given a common portion of the spectrum by the Federal Communications Commission.

Dual-Function Radar Communication Systems: A solution to the spectrum congestion problem

Abstract: To get the most use out of scarce spectrum, technologies have emerged that permit single systems to accommodate both radar and communications functions. Dual-function radar communication (DFRC) systems, where the two systems use the same platform and share the same hardware and spectral resources, form a specific class of radio-frequency (RF) technology. These systems support applications where communication data, whether as target and waveform parameter information or as information independent of the radar operation, are efficiently transmitted using the same radar aperture and frequency bandwidth. This is achieved by embedding communication signals into radar pulses. In this article, we review the principles of DFRC systems and describe the progress made to date in devising different forms of signal embedding. Various approaches to DFRC system design, including downlink and uplink signaling schemes, are discussed along with their respective benefits and limitations. We present tangible applications of DFRC systems and delineate their design requirements and challenges. Future trends and open research problems are also highlighted.

Robust Adaptive Beamforming Based on Steering Vector Estimation With as Little as Possible Prior Information

Abstract: A general notion of robustness for robust adaptive beamforming (RAB) problem and a unified principle for minimum variance distortionless response (MVDR) RAB techniques design are formulated. This principle is to use standard MVDR beamformer in tandem with an estimate of the desired signal steering vector found based on some imprecise prior information. Differences between various MVDR RAB techniques occur only because of the differences in the assumed prior information and the corresponding signal steering vector estimation techniques. A new MVDR RAB technique, which uses as little as possible and easy to obtain imprecise prior information, is developed. The objective for estimating the steering vector is the maximization of the beamformer output power, while the constraints are the normalization condition and the requirement that the estimate does not converge to any of the interference steering vectors and their linear combinations. The prior information used is only the imprecise knowledge of the antenna array geometry and angular sector in which the actual steering vector lies. Mathematically, the proposed MVDR RAB is expressed as the well known non-convex quadratically constrained quadratic programming problem with two constraints, which can be efficiently and exactly solved. Some new results for the corresponding optimization problem such as a new algebraic way of finding the rank-one solution from the general-rank solution of the relaxed problem and the condition under which the solution of the relaxed problem is guaranteed to be rank-one are derived. Our simulation results demonstrate the superiority of the proposed method over other previously developed RAB techniques.

Joint Radar and Communication Design: Applications, State-of-the-Art, and the Road Ahead

Abstract: Sharing of the frequency bands between radar and communication systems has attracted substantial attention, as it can avoid under-utilization of otherwise permanently allocated spectral resources, thus improving efficiency. Further, there is increasing demand for radar and communication systems that share the hardware platform as well as the frequency band, as this not only decongests the spectrum, but also benefits both sensing and signaling operations via the full cooperation between both functionalities. Nevertheless, the success of spectrum and hardware sharing between radar and communication systems critically depends on high-quality joint radar and communication designs. In the first part of this paper, we overview the research progress in the areas of radar-communication coexistence and dual-functional radar-communication (DFRC) systems, with particular emphasis on application scenarios and technical approaches. In the second part, we propose a novel transceiver architecture and frame structure for a DFRC base station (BS) operating in the millimeter wave (mmWave) band, using the hybrid analog-digital (HAD) beamforming technique. We assume that the BS is serving a multi-antenna user equipment (UE) over a mmWave channel, and at the same time it actively detects targets. The targets also play the role of scatterers for the communication signal. In that framework, we propose a novel scheme for joint target search and communication channel estimation, which relies on omni-directional pilot signals generated by the HAD structure. Given a fully-digital communication precoder and a desired radar transmit beampattern, we propose to design the analog and digital precoders under non-convex constant-modulus (CM) and power constraints, such that the BS can formulate narrow beams towards all the targets, while pre-equalizing the impact of the communication channel. Furthermore, we design a HAD receiver that can simultaneously process signals from the UE and echo waves from the targets. By tracking the angular variation of the targets, we show that it is possible to recover the target echoes and mitigate the resulting interference to the UE signals, even when the radar and communication signals share the same signal-to-noise ratio (SNR). The feasibility and efficiency of the proposed approaches in realizing DFRC are verified via numerical simulations. Finally, the paper concludes with an overview of the open problems in the research field of communication and radar spectrum sharing (CRSS).

Massive MIMO is a reality—What is next?: Five promising research directions for antenna arrays

Abstract: Massive MIMO (multiple-input multiple-output) is no longer a “wild” or “promising” concept for future cellular networks—in 2018 it became a reality. Base stations (BSs) with 64 fully digital transceiver chains were commercially deployed in several countries, the key ingredients of Massive MIMO have made it into the 5G standard, the signal processing methods required to achieve unprecedented spectral efficiency have been developed, and the limitation due to pilot contamination has been resolved. Even the development of fully digital Massive MIMO arrays for mmWave frequencies—once viewed prohibitively complicated and costly—is well underway. In a few years, Massive MIMO with fully digital transceivers will be a mainstream feature at both sub-6 GHz and mmWave frequencies. In this paper, we explain how the first chapter of the Massive MIMO research saga has come to an end, while the story has just begun. The coming wide-scale deployment of BSs with massive antenna arrays opens the door to a brand new world where spatial processing capabilities are omnipresent. In addition to mobile broadband services, the antennas can be used for other communication applications, such as low-power machine-type or ultra-reliable communications, as well as non-communication applications such as radar, sensing and positioning. We outline five new Massive MIMO related research directions: Extremely large aperture arrays, Holographic Massive MIMO, Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive MIMO.

Toward Dual-functional Radar-Communication Systems: Optimal Waveform Design

Abstract: We focus on a dual-functional multi-input-multi-output (MIMO) radar-communication (RadCom) system, where a single transmitter with multiple antennas communicates with downlink cellular users and detects radar targets simultaneously. Several design criteria are considered for minimizing the downlink multiuser interference. First, we consider both omnidirectional and directional beampattern design problems, where the closed-form globally optimal solutions are obtained. Based on the derived waveforms, we further consider weighted optimizations targeting a flexible tradeoff between radar and communications performance and introduce low-complexity algorithms. Moreover, to address the more practical constant modulus waveform design problem, we propose a branch-and-bound algorithm that obtains a globally optimal solution, and derive its worst-case complexity as function of the maximum iteration number. Finally, we assess the effectiveness of the proposed waveform design approaches via numerical results.

Robust Adaptive Beamforming Based on Interference Covariance Matrix Reconstruction and Steering Vector Estimation

Abstract: Adaptive beamformers are sensitive to model mismatch, especially when the desired signal is present in training snapshots or when the training is done using data samples. In contrast to previous works, this correspondence attempts to reconstruct the interference-plus-noise covariance matrix instead of searching for the optimal diagonal loading factor for the sample covariance matrix. The estimator is based on the Capon spectral estimator integrated over a region separated from the desired signal direction. This is shown to be more robust than using the sample covariance matrix. Subsequently, the mismatch in the steering vector of the desired signal is estimated by maximizing the beamformer output power under a constraint that prevents the corrected steering vector from getting close to the interference steering vectors. The proposed adaptive beamforming algorithm does not impose a norm constraint. Therefore, it can be used even in applications where gain perturbations affect the steering vector. Simulation results demonstrate that the performance of the proposed adaptive beamformer is almost always close to the optimal value across a wide range of signal to noise and signal to interference ratios.

MU-MIMO Communications With MIMO Radar: From Co-Existence to Joint Transmission

Abstract: Beamforming techniques are proposed for a joint multi-input-multi-output (MIMO) radar-communication (RadCom) system, where a single device acts as radar and a communication base station (BS) by simultaneously communicating with downlink users and detecting radar targets. Two operational options are considered, where we first split the antennas into two groups, one for radar and the other for communication. Under this deployment, the radar signal is designed to fall into the null-space of the downlink channel. The communication beamformer is optimized such that the beampattern obtained matches the radar’s beampattern while satisfying the communication performance requirements. To reduce the optimizations’ constraints, we consider a second operational option, where all the antennas transmit a joint waveform that is shared by both radar and communications. In this case, we formulate an appropriate probing beampattern, while guaranteeing the performance of the downlink communications. By incorporating the SINR constraints into objective functions as penalty terms, we further simplify the original beamforming designs to weighted optimizations, and solve them by efficient manifold algorithms. Numerical results show that the shared deployment outperforms the separated case significantly, and the proposed weighted optimizations achieve a similar performance to the original optimizations, despite their significantly lower computational complexity.