A reconfigurable intelligent surface (RIS) is a nearly-passive flat layer made of inexpensive elements that can add a tunable phase shift to the impinging electromagnetic wave and are controlled by a low-power electronic circuit. This paper considers the fundamental problem of target detection in a RIS-aided multiple-input multiple-output (MIMO) radar. At first, a general signal model is introduced, which includes the possibility of using up to two RISs (one close to the radar transmitter and one close to the radar receiver) and subsumes both a monostatic and a bistatic radar configuration with or without a line-of-sight view of the prospective target. Upon resorting to a generalized likelihood ratio test (GLRT), the design of the phase shifts introduced by the RIS elements is formulated as the maximization of the probability of detection in the location under inspection for a fixed probability of false alarm, and suitable optimization algorithms are proposed. The performance analysis shows the benefits granted by the presence of the RISs and shed light on the interplay among the key system parameters, such as the radar-RIS distance, the RIS size, and the location of the prospective target. A major finding is that the RISs should be better deployed in the near-field of the radar arrays at both the transmit and the receive side. The paper is concluded by discussing some open problems and foreseen applications.

We consider a multicell orthogonal frequency-division multiple-access (OFDMA) wireless network with universal frequency reuse and treat the problem of cochannel interference mitigation via base station coordination in the downlink. Assuming that coordinated access points only share channel quality measurements but not user data symbols, we propose to select the set of cochannel users and the power allocation across tones to maximize the weighted system sum rate subject to per-base-station power constraints. Since this is a nonconvex combinatorial problem, efficient suboptimal algorithms are presented and discussed, each requiring a different level of coordination among base stations and a different feedback signaling overhead. Simulation results are provided to assess the performances of the proposed strategies.

This paper addresses the problem of energy-efficient resource allocation in the downlink of a cellular orthogonal frequency division multiple access system. Three definitions of energy efficiency are considered for system design, accounting for both the radiated and the circuit power. User scheduling and power allocation are optimized across a cluster of coordinated base stations with a constraint on the maximum transmit power (either per subcarrier or per base station). The asymptotic noise-limited regime is discussed as a special case. Results show that the maximization of the energy efficiency is approximately equivalent to the maximization of the spectral efficiency for small values of the maximum transmit power, while there is a wide range of values of the maximum transmit power for which a moderate reduction of the data rate provides large savings in terms of dissipated energy. In addition, the performance gap among the considered resource allocation strategies is reduced as the out-of-cluster interference increases.

In this paper we present a novel procedure for multi-frame detection in radar systems. The proposed architecture consists of a pre-processing stage, which extracts a set of candidate alarms (or plots) from the raw data measurements (e.g., this can be the Detector and Plot-Extractor of common radar systems), and a track-before-detect (TBD) processor, which jointly elaborates observations from multiple scans (or frames) and confirms reliable plots. A computationally efficient dynamic programming algorithm for the TBD processor is derived, which does not require a discretization of the state space and operates directly on the input plot-lists. Finally, a simple algorithm to solve possible data association problems arising at the track-formation step is given, and a thorough complexity and performance analysis is provided, showing that large detection gains with respect to the standard radar processing are achievable with negligible complexity increase.

We consider a multi-cell wireless network with universal frequency reuse and treat the problem of co-channel interference mitigation in the downlink channel. Assuming that each base station serves multiple single-antenna mobiles via space-division multiple-access, we jointly optimize the linear beam-vectors across a set of coordinated cells and resource slots: the objective function to be maximized is the instantaneous weighted sum-rate subject to per-base-station power constraints. After deriving the general structure of the optimal beam-vectors, a novel iterative algorithm is presented which attempts to solve the Karush-Kuhn-Tucker conditions of the non-convex problem at hand. The proposed algorithm admits a distributed implementation which we illustrate. Also, various approaches to choose the initial beam-vectors are considered, one of which maximizes the signal-to-leakage-plus-noise ratio. Finally, simulation results are provided to assess the performance of the proposed algorithm.

In this paper we present a family of track-before-detect (TBD) procedures for early detection of moving targets from airborne radars. Upon a sectorization of the coverage area, the received echoes are jointly processed in the azimuth-range-Doppler domain and in the time domain through a Viterbi-like algorithm that exploits the physically admissible target transitions between successive illuminations, in order to collect all of the energy back-scattered during the time on target (TOT). A reduced-complexity implementation is derived assuming, at the design stage, that the target does not change resolution cell during the TOT in each scan. The constant false alarm rate (CFAR) constraint is also englobed in the proposed procedures as well as the possibility of working with quantized data. Simulation results show that the proposed algorithms have good detection and tracking capabilities even for high target velocities and low quantization rates.