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WThis paper considers a monostatic multiple-input multipleoutput (MIMO) radar aided by a reconfigurable intelligent surface (RIS). After modeling the received target signal as the superposition of four echoes, which may involve up to two bounces off the RIS, the phases of the reflecting elements and the radar receive filter are chosen to maximize the signalto-noise ratio (SNR). Some examples are provided to assess the performance of this novel architecture

Increased amounts of bandwidth are required to guarantee both high-quality/high-rate wireless services (4G and 5G) and reliable sensing capabilities such as automotive radar, air traffic control, earth geophysical monitoring and security applications. Therefore, co-existence between radar and communication systems using overlapping bandwidths has been a primary investigation field in recent years. Various signal processing techniques such as interference mitigation, pre-coding or spatial separation, and waveform design allow both radar and communications to share the spectrum. This article reviews recent work on co-existence between radar and communication systems, including signal models, waveform design and signal processing techniques. Our goal is to survey contributions in this area in order to provide a primary starting point for new researchers interested in these problems., Comment: Submitted to IEEE Signal Processing Magazine

This monograph is devoted to random-set theory, which allows unordered collections of random elements, drawn from an arbitrary space, to be handled. After illustrating its foundations, we focus on Random Finite Sets, i.e., unordered collections of random cardinality of points from an arbitrary space, and show how this theory can be applied to a number of problems arising in wireless communication systems. Three of these problems are: (1) neighbor discovery in wireless networks, (2) multiuser detection in which the number of active users is unknown and time-varying, and (3) estimation of multipath channels where the number of paths is not known a priori and which are possibly time-varying. Standard solutions to these problems are intrinsically suboptimum as they proceed either by assuming a fixed number of vector components, or by first estimating this number and then the values taken on by the components. It is shown how random-set theory provides optimum solutions to all these problems. The complexity issue is also examined, and suboptimum solutions are presented and discussed.

Publication in the conference proceedings of EUSIPCO, Florence, Italy, 2006

In this paper a two-stage maximum-likelihood (ML) detection structure for group detection in DS/CDMA systems is presented. The first stage of the receiver is a linear filter, aimed at suppressing the effect of the unwanted (i.e., out-of-group) users' signals, while the second stage is a non-linear block, implementing a ML detection rule on the set of desired users signals. As to the linear stage, we consider both the decorrelating and the minimum mean square error approaches. Interestingly, the proposed detection structure turns out to be a generalization of Varanasi's group detector, to which it reduces when the system is synchronous, the signatures are linearly independent and the first stage of the receiver is a decorrelator. The issue of blind adaptive receiver implementation is also considered, and implementations of the proposed receiver based on the LMS algorithm, the RLS algorithm and subspace-tracking algorithms are presented. These adaptive receivers do not rely on any knowledge on the out-of-group users' signals, and are thus particularly suited for rejection of out-of-cell interference in the base station. Simulation results confirm that the proposed structure achieves very satisfactory performance in comparison with previously derived receivers, as well as that the proposed blind adaptive algorithms achieve satisfactory performance.

Comunicació presentada en la 16th European Signal Processing Conference (EUSIPCO 2008), celebrada els dies 25, 26, 27, 28 i 29 d’agost de 2008 a Lausana (Suïssa), organitzada per la European Association for Signal Processing (EURASIP). This paper presents several algorithms for joint estimation of the target number and state in a time-varying scenario. Building on the results presented in [1], which considers estimation of the target number only, we assume that not only the target number, but also their state evolution must be estimated. In this context, we extend to this new scenario the Rao-Blackwellization procedure of [1] to compute Bayes recursions, thus defining reduced-complexity solutions for the multi-target set estimator. A performance assessment/nis finally given both in terms of Circular Position Error Probability - aimed at evaluating the accuracy of the estimated track - and in terms of Cardinality Error Probability, aimed at evaluating the reliability of the target number estimates.

Increased amounts of bandwidth are required to guarantee both high-quality/high-rate wireless services (4G and 5G) and reliable sensing capabilities, such as for automotive radar, air traffic control, earth geophysical monitoring, and security applications. Therefore, coexistence between radar and communication systems using overlapping bandwidths has come to be a primary investigation field in recent years. Various signal processing techniques, such as interference mitigation, precoding or spatial separation, and waveform design, allow both radar and communications to share the spectrum. This article reviews recent work on coexistence between radar and communication systems, including signal models, waveform design, and signal processing techniques. Our goal is to survey contributions in this area to provide a primary starting point for new researchers interested in these problems.

Energy efficiency, possibly coupled with cognition-based and spectrum-sharing architectures, is a key enabling technology for green communications in 5G-and-beyond standards. In this context, the present paper considers a multiple-input multiple-output communication system cooperatively coexisting with a surveillance radar: the objective function is the communication system energy efficiency, while radar operation is safeguarded by constraining the minimum received signal-to-disturbance ratio for a set of range-azimuth cells of the controlled scene, and no time synchronization between them is assumed. The degrees of freedom are the transmit powers of both systems, the space-time communication codebook and the linear filters at the radar receiver. The resulting optimization problem is non-convex, due to both the objective function and the presence of signal-dependent interference (clutter): we develop a block-coordinate-ascent approximate solution, and offer a thorough performance assessment, so as to elicit the merits of the proposed approach, along with the interplay among the achievable energy efficiency, the density of scatterers in the environment, and the size of the set of protected radar cells., Accepted (with minor changes) in the IEEE Transactions on Signal Processing. arXiv admin note: text overlap with arXiv:1907.07943

This paper considers the joint design of a multiple-input multiple-output (MIMO) radar with co-located antennas and a MIMO communication system. The degrees of freedom under the designer's control are the waveforms transmitted by the radar transmit array, the filter at the radar array and the code-book employed by the communication system to form its space-time code matrix. Two formulations of the spectrum sharing problem are proposed. First, the design problem is stated as the constrained maximization of the signal-to-interference-plus-noise ratio at the radar receiver, where interference is due to both clutter and the coexistence structure, and the constraints concern both the similarity with a standard radar waveform and the rate achievable by the communication system, on top of those on the transmit energy. The resulting problem is nonconvex, but a reduced-complexity iterative algorithm, based on iterative alternating maximization of three suitably designed subproblems, is proposed and analyzed. In addition, the constrained maximization of the communication rate is also investigated. The convergence of all the devised algorithms is guaranteed. Finally, a thorough performance assessment is presented, aimed at showing the merits of the proposed approach.

Complex ADMM-Net, a complex-valued neural network architecture inspired by the alternating direction method of multipliers (ADMM), is designed for interference removal in super-resolution stepped frequency radar angle-range-doppler imaging. Tailored to an uncooperative scenario wherein a MIMO radar shares spectrum with communications, the ADMM-Net recovers the radar image---which is assumed to be sparse---and simultaneously removes the communication interference, which is modeled as sparse in the frequency domain owing to spectrum underutilization. The scenario motivates an $\ell_1$-minimization problem whose ADMM iteration, in turn, undergirds the neural network design, yielding a set of generalized ADMM iterations that have learnable hyperparameters and operations. To train the network we use random data generated according to the radar and communication signal models. In numerical experiments ADMM-Net exhibits markedly lower error and computational cost than ADMM and CVX.

This paper considers the uplink of a massive MIMO communication system using 5G New Radio-compliant multiple access, which is to co-exist with a radar system using the same frequency band. A system model taking into account the reverberation (clutter) produced by the radar system onto the massive MIMO receiver is proposed. In this scenario, several receivers for uplink channel estimation and data detection are proposed, ranging from the simple channel-matched beamformer to the zero-forcing and linear minimum mean square error receivers for clutter disturbance rejection, under the two opposite situations of perfectly known ad completely unknown clutter covariance. A theoretical analysis is also given, deriving a lower bound on the achievable uplink spectral efficiency and the mutual information between the input Gaussian-encoded symbols and the observables available at the communication receiver of the cellular massive MIMO system: regarding the latter, in particular, we show that, in the large antenna number regime, the radar clutter effects at the base station is suppressed and single-user capacity is restored. Numerical results, illustrating the performance of the proposed detection schemes, confirm the findings of the theoretical analysis, and permit quantifying the system robustness to clutter effect for increasing number of antennas at the base station., Comment: 15 pages, 8 figures, paper accepted for publication in IEEE Transactions on Wireless Communications. arXiv admin note: text overlap with arXiv:1805.07796

This paper proposes computationally efficient algorithms to maximize the energy efficiency in multi-carrier wireless interference networks, by a suitable allocation of the system radio resources, namely the transmit powers and subcarrier assignment. The problem is formulated as the maximization of the system Global Energy-Efficiency subject to both maximum power and minimum rate constraints. This leads to a challenging non-convex fractional problem, which is tackled through an interplay of fractional programming, learning, and game theory. The proposed algorithmic framework is provably convergent and has a complexity linear in both the number of users and subcarriers, whereas other available solutions can only guarantee a polynomial complexity in the number of users and subcarriers. Numerical results show that the proposed method performs similarly as other, more complex, algorithms.

The paper studies the scenario in which a multiple-input multiple-output (MIMO) radar coexists with a MIMO wireless communication system in the presence of clutter. The radar space-time transmit code, the radar space-time receive filter, and the communication space-time transmit covariance matrix are jointly optimized. An iterative procedure is developed to maximize the radar output signal to interference plus noise ratio (SINR) under the constraints of the communication rate, the radar waveform similarity and the power of radar and communication. Numerical results highlight the applicability of the proposed method in different scenarios.

In this work, we focus on vehicular networks employing the IEEE 802.11ad standard and show the feasibility of an opportunistic radar system. The echo generated by the beacon transmitted during the sector level sweep of the beamforming protocol is exploited to perform target detection and range/velocity estimation. Two solutions, which differ in the amount of prior information on the transmitted waveform, are developed, and numerical results showing their detection and estimation performance are provided.

Spectrum sensing for cognitive-radio applications may use a matched-filter detector (in the presence of full knowledge of the signal that may be transmitted by the primary user) or an energy detector (when that knowledge is missing). An intermediate situation occurs when the primary signal is imperfectly known, in which case we advocate the use of a linear-quadratic detector. We show how this detector can be designed by maximizing its deflection, and, using moment-bound theory, we examine its robustness to the variations of the actual probability distribution of the inaccurately known primary signal.

In this work, we study the fundamental tradeoff between integration time and scan rate in radar systems. The contrasting needs for a large probability of detection and a short scan time are carefully balanced by optimizing the detection rate, defined as the average number of detections from a target per unit of time. A closed-form solution for the optimum pulse train length is provided in the relevant case of Gaussian observations with unknown noise variance. Some examples are given to show the possible tradeoffs among the principal system parameters.

In this work, we study the achievable performance of a sea-search radar when the transmit beam-with is varied so as to trade a lower directional gain for a longer time-on-target and/or a shorter scan duration due to the reduced number of scanned directions. The considered figure of merit is the number of target detections per unit of time, which allows a fair comparison among scanning policies with different duration, under a constraint on the average number of false alarms per unit of time from the monitored area and on the maximum time-on-target. Examples are provided to show the possible trade-offs as function of the signal-to-clutter and signal-to-noise ratios.

The problem of determining which sensors are neighbors of a given one in a wireless network operating on a frequency-flat Gaussian channel is considered. While recent neighbor discovery (ND) algorithms operate at protocol level, the developed schemes exploit signal processing techniques to perform ND at physical layer. Similarly to the existing approaches, it is assumed that sensors transmit at random instants copy of the signature waveform associated to their identities. Borrowing techniques from multiuser detection, it turns out that the developed ND algorithms can handle multi-sensor interference environments where protocol level algorithms entail waste of energy due to packet collisions. A number of neighbor discovery algorithms based on different optimization criteria are introduced and analyzed. Numerical results show that reduced complexity algorithms can achieve a satisfactory performance.

Recently, a new class of linear multiuser receivers for direct-sequence code-division multiple-access (CDMA) systems employing binary phase-shift keying modulation has been introduced. Unlike classical decorrelating and minimum mean-square error linear multiuser detectors, the new receivers exploit the information contained in the pseudo-autocorrelation of the observables, and are, thus, capable of achieving much better performance. We present new results on the performance analysis of this class of new receivers. In particular, with reference to a CDMA system with deterministic spreading codes, we show that the new receivers outperform the classical ones in terms of both error probability and near-far resistance. With regard, instead, to CDMA systems with random spreading, we compute the average system near-far resistance, showing that the new receivers can accommodate twice the number of users accommodated by the classical linear multiuser receivers.

In this work we introduce a novel track formation procedure to overcome the performance losses of the two-stage track-before-detect architecture in [1] when targets are closely-spaced. The proposed strategy adopts a dynamic programming algorithm which successively estimates the trajectories of prospective targets and removes the corresponding measurements from the input data, and which does not need a discretization of the state space. Experimental results demonstrate that its detection capabilities are almost independent of the mutual distance of the targets and equal to those of the system in [1] when targets are widely-spaced.

The authors consider procedures for constant false alarm rate in lognormal clutter, accounting for variations of both the scale and a shape parameter of the clutter. Adaptivity to both parameters is obtained through biparametric estimation based on a sliding window surrounding the radar cell under test. Some procedures exploiting best linear unbiased estimation (BLUE) are presented and compared to a previous procedure called Log-t, which uses maximum likelihood estimation (MLE). The comparison is carried on for both a homogeneous clutter environment and for instances of inhomogeneous environment (clutter edges and spurious targets). In the latter instances, some advantages of BLUE procedures which stem from the opportunity of censoring are highlighted. >

In this paper we propose and assess TBD strategies for radar systems adopting STAP. At the design stage we consider a radar system equipped with a linear array of Na sensors that illuminates the surveillance area by transmitting M coherent pulse trains, each consisting of Np pulses, before deciding whether or not a target is present over L adjacent range cells. As a preliminary step we introduce the target and noise models. Then, resorting to GLRT and ad hoc procedures, we derive adaptive CFAR detectors for both stationary and scan-to-scan varying clutter scenarios (a point better clarified in the body of the paper). The proposed detectors guarantee the CFAR property with respect to the unknown spectral properties of the clutter. The preliminary performance assessment, conducted resorting to Monte Carlo simulation, shows that proposed procedures might be a viable means to implement early detection and track initiation of weak moving targets.