Luca Venturino

Coordinated Scheduling and Power Allocation in Downlink Multicell OFDMA Networks

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.

Coordinated linear beamforming in downlink multi-cell wireless networks

We consider the problem of co-channel interference mitigation in a downlink multi-cell wireless network. Assuming that each access point serves multiple single-antenna mobiles via space division multiple access (SDMA), we jointly optimize the linear beam-vectors across a set of coordinated cells and resource slots: the objective function to be maximized is the weighted system 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 (KKT) conditions of the non-convex primal problem at hand. Simulation results are provided to assess the performance of the proposed algorithm.

Energy-Efficient Scheduling and Power Allocation in Downlink OFDMA Networks With Base Station Coordination

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.

Multiuser detection for cooperative networks and performance analysis

We investigate strategies for user cooperation in the uplink of a synchronous direct-sequence code-division multiple-access (DS/CDMA) network employing nonorthogonal spreading codes and analyze their performance. We consider two repetition-based relay schemes: decode-and-forward (DAF) and amplify-and-forward (AAF). Focusing on the use of linear multiuser detectors, we first present cooperation strategies, i.e., signal processing at both the relay nodes and the base station (BS), under the assumption of perfectly known channel conditions of all links; then, we consider the more practical scenario where relays and BS have only partial information about the system parameters, which requires blind multiuser detection methods. We provide performance analysis of the proposed detection strategies in terms of the (asymptotic) signal-to-(interference plus noise) ratio and the bit error rate, and we show that AAF achieves a full second-order diversity when a minimum mean-square-error detector is employed at both the relay side and the BS. A simple, yet effective, partner selection algorithm is also presented. Finally, a thorough performance assessment is undertaken to study the impact of the multiple-access interference on the proposed cooperative strategies under different scenarios and system assumptions

Track-before-detect procedures for early detection of moving target from airborne radars

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.

Track-before-detect procedures in a multi-target environment

This paper addresses the problem of early detection of K ges 1 multiple moving targets in radar systems through the use of track-before-detect (TBD) techniques. At first, assuming prior knowledge of K, a binary generalized likelihood ratio test (GLRT) is derived, which shows that the multi-target TBD problem can be regarded as a K-path trellis search. Since optimal implementation of the GLRT has a nonlinear complexity either in the number of targets or in the number of integrated frames, suboptimum algorithms are investigated which allow to trade better estimation and tracking accuracy for a much lower implementation complexity. Next, the TBD problem with K unknown is discussed and a novel multi-hypothesis test strategy is derived as the solution to a constrained optimization problem, which subsumes the conventional binary GLRT as the special case of known K. Finally, numerical examples are provided to assess and compare the performances of the proposed TBD procedures.

Weighted Sum-Rate Maximization in Multi-Cell Networks via Coordinated Scheduling and Discrete Power Control

Inter-cell interference mitigation is a key challenge in the next generation wireless networks which are expected to use an aggressive frequency reuse factor and a high-density base station deployment to improve coverage and spectral efficiency. In this work, we consider the problem of maximizing the weighted sum-rate of a wireless cellular network via coordinated scheduling and discrete power control. We present two distributed iterative algorithms which require limited information exchange and data processing at each base station. Both algorithms provably converge to a solution where no base station can unilaterally modify its status (i.e., transmit power and user selection) to improve the weighted sum-rate of the network. Numerical studies are carried out to assess the performance of the proposed schemes in a realistic system based on the IEEE 802.16m specifications. Simulation results show that the proposed algorithms achieve a significant rate gain over uncoordinated transmission strategies for both cell-edge and inner users.

A Novel Dynamic Programming Algorithm for Track-Before-Detect in Radar Systems

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.

Track-Before-Detect Strategies for STAP Radars

In this correspondence we propose track-before-detect (TBD) strategies for space-time adaptive processing (STAP) radars. As a preliminary step we introduce the target and noise models in discrete-time form. Then, resorting to generalized likelihood ratio test (GLRT)-based and ad hoc procedures we derive detectors for two different scenarios (a point better clarified in the body of the correspondence). The preliminary performance assessment, conducted resorting to Monte Carlo simulation, shows that the proposed procedures might be viable means to implement early detection and track initiation of weak moving targets.

Diversity-Integration Tradeoffs in MIMO Detection

In this work, a MIMO detection problem is considered. At first, we derive the Generalized Likelihood Ratio Test (GLRT) for arbitrary transmitted signals and arbitrary time-correlation of the disturbance. Then, we investigate design criteria for the transmitted waveforms in both power-unlimited and power-limited systems and we study the interplay among the rank of the optimized code matrix, the number of transmit diversity paths and the amount of energy integrated along each path. The results show that increasing the rank of the code matrix allows generating a larger number of diversity paths at the price of reducing the average signal-to-clutter level along each path.