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In this work, we study the joint detection and localization of multiple delay- and Doppler-spread targets through an opportunistic radar exploiting mmWave communication signals. The problem is formulated as the identification of an unknown number of active subspaces in a large family of subspaces, accounting for the possible positions of potential targets in the delay-Doppler domain: the resulting testing problem is composite and multi-hypothesis. At first, we derive a solution based on the generalized information criterion (GIC), whose complexity is however prohibitive; then, we propose an approximated form of the GIC-based receiver and derive two iterative data-adaptive strategies, both extracting and eliminating the superimposed back-scattered subspace signals one-by-one. Leveraging the IEEE 802.11ad standard, a short-range low-mobility application is discussed to validate the merits of the proposed procedures in terms of detection and localization capabilities, robustness to multi-target interference, and achievable resolution.

In this work, we exploit the sector level sweep of the IEEE 802.11ad communication standard to implement an opportunistic radar at mmWaves and derive an adaptive procedure for detecting multiple targets (echoes) and estimating their parameters. The proposed detector/estimator extracts the prospective echoes one-by-one from the received signal, after removing the interference caused by the previously detected (stronger) targets. Examples are provided to assess the system performance, also in comparison with the canonical matched-filter peak-detector and the Cram\'er-Rao bounds. Results indicate that the proposed method is robust against the signal spillover and the near-far problem caused by the imperfect auto-correlation of the probing signal and, for the same probability of false alarm, grants detection and localization performances close to those previously obtained in a simplified single-target scenario., Comment: Journal paper submitted to the IEEE Transactions on Wireless Communications on April 19, 2019

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.

This paper handles the problem of optimizing the scanning policy of a surveillance system in the presence of Rayleigh targets in a mixture of K -distributed clutter and Gaussian noise. Adopting the detection rate (DR) and false alarm rate (FAR) as performance measures, we show that the said optimization amounts to solving a constrained DR maximization, wherein the free parameters are the transmit beamwidth, the dwell time, and the detection threshold, whereas the constraints concern the maximum FAR and time on target. A thorough performance assessment is offered, aimed at eliciting the influence of the signal-to-noise and clutter-to-noise ratios, the clutter shape parameter, and the rate of change of the target response. The results indicate that, although a uniformly optimum transmit policy does not exist, some trends can be devised, which appears of particular relevance especially for systems that can avail themselves of some degree of cognition.

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.

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 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.

In random-access communication systems, the number of active users varies with time, and has considerable bearing on receiver's performance. Thus, techniques aimed at identifying not only the information transmitted, but also that number, play a central role in those systems. An example of application of these techniques can be found in multiuser detection (MUD). In typical MUD analyses, receivers are based on the assumption that the number of active users is constant and known at the receiver, and coincides with the maximum number of users entitled to access the system. This assumption is often overly pessimistic, since many users might be inactive at any given time, and detection under the assumption of a number of users larger than the real one may impair performance. The main goal of this paper is to introduce a general approach to the problem of identifying active users and estimating their parameters and data in a random-access system where users are continuously entering and leaving the system. The tool whose use we advocate is Random-Set Theory: applying this, we derive optimum receivers in an environment where the set of transmitters comprises an unknown number of elements. In addition, we can derive Bayesian-filter equations which describe the evolution with time of the a posteriori probability density of the unknown user parameters, and use this density to derive optimum detectors. In this paper we restrict ourselves to interferer identification and data detection, while in a companion paper we shall examine the more complex problem of estimating users' parameters., Comment: To be published on IEEE Transactions on Information Theory

In a recent paper, closed-form formulas for the Cramer-Rao bounds (CRBs) on the error variance of any unbiased estimator of the amplitudes, timing offsets, phase offsets, and directions-of-arrival (DoAs) of multiplexed asynchronous direct-sequence code division multiple access (DS/CDMA) signals adopting aperiodic spreading codes have been derived. These formulas depend on the active users' spreading codes and pilot information symbols. In this paper, we obtain formulas for the modified CRB under the assumption that the spreading codes can be modeled as random nuisance parameters. Moreover, we also consider the case that the timing offsets are modeled as random variates and provide formulas for the hybrid CRB, i.e., the CRB corresponding to the situation that some of the parameters to be estimated are random variates rather than unknown deterministic quantities. Numerical examples showing the impact of the training length, signal-to-noise ratio (SNR), and the number of active users on the CRB are also reported and commented upon.

In a Dual-Rate DS/CDMA system, a primary, ``high rate'' network coexists with a secondary one with a slower rate. Demultiplexing high-rate users typically entails, at the receiver end, a time-varying processing if Variable Spreading Length (VSL), Variable Chip Rate (VCR), or Variable Chip Rate with Frequency Shift (VCRFS) modulation formats are used, and Rake-Type demodulation schemes if the chip rate exceeds the channel coherence bandwidth. The realization of fully adaptive receivers thus requires the joint estimation of (a) the interference to be suppressed, whether from other users of the high-rate network or from the secondary network, and (b) the channel tap weights. The solution that we consider here assumes that, for each user, a pilot signal is transmitted along with the information-bearing signal, whether in a time-multiplexed or in a parallel-channel format. We consider both the uplink and the downlink channel and, based on a Minimum-Mean-Square-Error (MMSE) optimality criterion, we have come up with a fully adaptive system, capable on the one hand of tracking, through a cyclic Recursive-Least-Squares type algorithm, the periodically time-varying variations of the interference subspace and on the other of updating the channel tap weights estimates. A thorough performance assessment is presented, and the convergence dynamics of the system are derived through computer simulations in order to assess the impact of the prior uncertainty with regard to the other-users signatures and the channel tap weights realizations.

This paper addresses the problem of narrow-band interference (NBI) cancellation in direct-sequence spread-spectrum systems. The proposed procedure amounts to a preliminary nonlinear processing, wherein, upon projection of the received signal onto a Fourier basis, a number of samples having the largest modula are excluded from further processing. The structure of the optimum detector operating on censored observations is obtained, showing that the optimum detector performs matched filtering on the censored data. The performance assessment demonstrates that this receiver is able to suppress narrow-band interferers, no matter what their structure, provided that the censoring depth is properly chosen. A blind version of such a receiver is presented also, and a comparative performance assessment demonstrates that, unlike other suppression procedures, the proposed system allows suppression of NBI with no prior knowledge on its structure.

This paper handles the simultaneous suppression of narrow-band and multiaccess interference in code division multiple-access (CDMA) direct-sequence spread-spectrum (DSSS) systems. The basic structure we refer to is reminiscent of the decorrelating detector, but here the design strategy relies on the concept of combating jointly the two interference sources-precisely, a decision as to the bit transmitted by each user is made based on the projection of the observables onto the orthogonal complement to the subspace spanned by the other users' signatures and the narrow-band interference. We focus on several different implementations of such a strategy, assuming a different degree of prior knowledge as to the narrow-band interference. An important side result of the proposed approach is that, in general, complete suppression of data-like interference may be achieved through periodically time-varying processing. An adaptive version of such a receiver is also presented, wherein the projection direction is estimated based on suitable estimates of the covariance properties of the observables. The value of this method is also assessed by studying the rate of convergence of the estimated direction to the true projection direction.

The paper compares two newly proposed detection schemes for targets in K-distributed clutter: the first implements generalised likelihood ratio test, and the second represents a discrete realisation of the classical Neymann-Pearson detector. Results indicate that the two optimisation strategies yield substantially equivalent performance, but the generalised likelihood ratio test is simpler in its structure and offers some additional advantages both at the design and at the analysis stage.

The performance of the excision CFAR detector is investigated, accounting for a Swerling 2 model of the useful signal. This analysis supplements a recent paper in which the performance of the same detector is evaluated, assuming a Swerling 0 model for the useful signal

Exact expressions are derived for the ROCs of a CA-CFAR radar processor subject to both internal noise and clutter (the last one modelled as compound Gaussian). They include previously known ROCs, e.g. for ideal CFAR. The effect of finite sample size is elicited in the example of K-distributed clutter.

The main shortcoming of currently working CFAR procedures based on the slidingwindow concept is a substantial performance degradation in the presence of nonhomogeneous background interference. Alternative procedures, based on clutter maps, exploit the intrinsic local homogeneity of the radar environment, thus yielding enhanced robustness and, at the same time, little loss of detectability with respect to optimum detectors. The paper analyses one such procedure and shows that it works well under quite general conditions; plots are given of detection probability against the average signal-to-noise ratio for several values of false alarm probability. The problem of the self-masking target is also investigated and the performance impairment due to such phenomena is assessed; plots of detection performance against the number of scans for which the target persists in the same map cell are given for several values of the system parameters.