Giuseppe Abreu

Distributed GABBA space-time codes in amplify-and-forward relay networks

Cooperative communications via distributed space-time codes has been recently proposed as a way to form virtual multiple-antennas that provide dramatic gains in slow fading wireless environments. In this paper, we consider the design of practical distributed space-time codes for wireless relay networks using the amplify-and-forward (AF) scheme, where each relay transmits a scaled version of the linear combinations of the received symbols and their complex conjugate. We employ GABBA codes, which are systematically constructed, orthogonally decodable, full-rate, full-diversity space-time block codes, in a distributed fashion. Our scheme is valid for any number of relays with linear orthogonal decoding in the destination, which make it feasible to employ large numbers of potential relays to improve the diversity order. We generalize the distributed space-time codes in AF mode when the source-destination link contributes in both phases of the transmission. Assuming MPSK or M-QAM constellations and maximum likelihood (ML) detection, we derive an approximate formula for the symbol error probability of the investigated scheme in Rayleigh fading channels. The analytical results are confirmed by simulations, indicating both the accuracy of the analysis, and the fact that low-complexity, flexible, and high-performing distributed space-time block codes can be designed based on GABBA codes.

Combined Pulse Shape and Pulse Position Modulation for High Data Rate Transmissions in Ultra-Wideband Communications

In this paper we present a novel method for high data rate transmissions in ultra-wideband (UWB) communications systems. This is achieved through the combination of conventional pulse position modulation and pulse shape modulation schemes. The result is a pulse shape and position modulation that allows transmission of more bits of information in the same amount of time and using the same number of pulses as the conventional schemes. A feature of the proposed system is that the allowable alphabet is limited so as to ensure equal power in transmission of all symbols. Symbol size can also be easily changed without significantly changing the hardware of the system. Theoretical error performance analysis of this system is also provided.

On the design of orthogonal pulse-shape modulation for UWB systems using Hermite pulses

Orthogonal pulse-shape modulation using Hermite pulses for ultra-wideband communications is reviewed. Closed-form expressions of cross-correlations among Hermite pulses and their corresponding transmit and receive waveforms are provided. These show that the pulses lose orthogonality at the receiver in the presence of differentiating antennas. Using these expressions, an algebraic model is established based on the projections of distorted receive waveforms onto the orthonormal basis given by the set of normalized orthogonal Hermite pulses. Using this new matrix model, a number of pulse-shape modulation schemes are analyzed and a novel orthogonal design is proposed. In the proposed orthogonal design, transmit waveforms are constructed as combinations of elementary Hermites with weighting coefficients derived by employing the Gram-Schmidt (QR.) factorization of the differentiating distortion models matrix. The design ensures orthogonality of the vectors at the output of the receiver bank of correlators, without requiring compensation for the distortion introduced by the antennas. In addition, a new set of elementary Hermite Pulses is proposed which further enhances the performance of the new design while enabling a simplified hardware implementation.

On the Maximum Likelihood Approach for Source and Network Localization

We consider the source and network localization problems, seeking to strengthen the relationship between the Weighted-Least-Square (WLS) and the Maximum-Likelihood (ML) solutions of these problems. To this end, we design an optimization algorithm for source and network localization under the principle that: a) the WLS and the ML objectives should be the same; and b) the solution of the ML-WLS objective does not depend on any information besides the set of given distance measurements (observations). The proposed Range-Global Distance Continuation (R-GDC) algorithm solves the localization problems via iterative minimizations of smoothed variations of the WLS objective, each obtained by convolution with a Gaussian kernel of progressively smaller variances. Since the last (not smoothed) WLS objective derives directly from the ML formulation of the localization problem, and the R-GDC requires no initial estimate to minimize it, final result is maximum-likelihood approach to source and network localization problems. The performance of the R-GDC method is compared to that of state-of-the-art techniques such as semidefinite programming (SDP), nonlinear Newton least squares (NLS), and the Stress-of-a-MAjorizing-Complex-Objective-Function (SMACOF) algorithms, as well as to the Cramér-Rao Lower Bound (CRLB). The comparison reveals that the solutions obtained with the R-GDC algorithm is insensitive to initial estimates and provides a localization error that closely approaches that of the corresponding fundamental bounds. The R-GDC is also found to achieve a complexity order comparable to that of the SMACOF, which is known for its efficiency.

MAC Performances for Localization and Tracking in Wireless Sensor Networks

Time delay rather then throughput, is a constraint of greater importance in tracking systems. In particular, the maximum accces delay permissible by the application ins strongly related to the dynamics of theracked objects. The purpose of this article is to study the performance of a new media access control (MAC) technology specifically suited for LDR UWB systems [3] under the point of view of a tracking application. Specifically, the time delay necessary to collect the ranging information in both, star and meshed topology networks, have been studied as function of the number of mobiles in the network. More importantly, we propose two new ranging packet to be used inside the aforementioned MAC, in order to achieve in both the network topologies, a clear advantage compared to the current solution.

Indoor positioning: A key enabling technology for IoT applications

Motivated by the recent advances on internet of things (IoT) and the importance that location information has on many application scenarios, this article offers references to theoretical and localization-algorithmic tools that can be utilised in connection with IoT. We develop this discussion from basic to sophisticated localization techniques covering also some less-intuitive notions of localization, e.g. semantic positioning, for which we provide a novel solution which overcome the problem of privacy. We analyze the localization problem from a mathematical perspective; reviewing the most common and best-performing class of localization methods based on optimization and algebraic approaches and we discuss benefits of location information in a wireless system. In this regard we discuss few concrete applications scenario currently under investigation in the largest EU project on IoT, namely the FP-7 Butler project, how location information is one of the key enabling technology in the IoT. In addition to the theoretical aspect, this article provides references to the pervasive localization system architecture using the smart sensors developed within the Butler project.

Adaptive Gating for Multitarget Tracking With Gaussian Mixture Filters

In this correspondence, we use a generalization of the Bayesian approach to the multitarget problem that goes under the name of cardinalized probability hypothesis density (CPHD) filter to jointly estimate a time varying number of targets and their locations from sets of noisy range measurements. While in the case of Gaussian linear models a closed-form solution for the CPHD recursion exists in the form of a Gaussian mixture (GM), the more general case of nonlinear systems suboptimal solutions becomes necessary. Due to the Gaussianity assumption in the the GM-CPHD filter, we propose to integrate the square-root cubature Kalman filter (S-CKF) into the GM-CPHD recursion. A novel weighted gating strategy, which exploits the GM implementation of the proposed S-CKF-GM-CPHD filter, is offered to lower the computational time by adaptively increasing the gate sizes in proportion to the likelihood of the single GM components. The results reveal that the proposed gating yields considerable savings in processing requirements compared to no gating, without any significant degradation in performance. In addition, although the run time improvement achieved with elliptical or adaptive gating is equivalent, the latter does not degrade the results.

Closed-Form Hop-Count Distributions in Random Networks with Arbitrary Routing

We contribute a new solution to the problem of establishing an analytical relationship between hop-counts under a certain routing policy and Euclidean distances in random networks, both in the linear and planar cases. The contributed solution is unified, in that hop-count distributions have similar expressions both in the 1D and the 2D cases; general in terms of routing policies, in that the effect of any given policy is accounted for by means of a single parameter; closed-form, such that hop-count probability mass functions (PMFs) are given in terms of scaled versions of the closed-form PMFs of the number of nodes; and mathematically tractable, since the derived hop-count distributions are in the form of a difference of the well-known Nakagami-m cumulative density functions (CDFs). Direct and Kullback-Leibler divergence comparisons against empirical data demonstrate the high accuracy of our solution. The simplicity, accuracy and generality of the result owes partly to a self-imposed confinement to connected networks, defined formally in stochastic-geometric terms, which allows for the elimination of recursions and multivariate marginalization commonly required by existing solutions. The contributed results find application in the design and analysis of ad hoc networks, cooperative localization algorithms or latency and energy consumption analysis.

Understanding and Solving Flip-Ambiguity in Network Localization via Semidefinite Programming

We employ the semidefine programming (SDP) framework to first analyze, and then solve, the problem of flip-ambiguity afflicting range-based network localization algorithms with incomplete ranging information. First, we study the occurrence of flip-ambiguous nodes and errors due to flip ambiguity by considering random network topologies with successively smaller connectivity ranges RMax >RMax - ΔR >. . . >RU >RL, and employing an SDP-based unique localizability test to detect the limiting connectivity ranges RU and RL that are respectively sufficient and un-sufficient to ensure unique localizability. Then, we utilize this information to construct an SDP formulation of the localization problem with Genie-aided constraints, which is shown to resolve flip-ambiguities. Finally, we derive a flip-ambiguity-robust network localization algorithm by relaxing the Genie-aided constraints onto feasible alternatives. Finally, the performance of the so-obtained localization algorithm is studied by Monte-Carlo simulations, which reveal a substantial improvement over the conventional SDP-based algorithm.

Efficient and accurate localization in multihop networks

We present evidence that multihop node-to-anchor distance information is sufficient to allow accurate self-localization in multihop wireless networks (such as ad hoc and sensor networks, as well as future cellular systems based on LTE). To this purpose we have implemented two new distance-based source localization algorithms, which prove highly robust to inaccurate range information characterized by distance estimates exceeding the correct ones. Our contribution is a contrasting alternative to current distributed self-localization algorithms, which are founded on the idea of “diffusing” the known location of a few nodes (anchor) to the entire the network via a typically large number of message exchanges amongst neighbors, resulting in high communications costs, low robustness to mobility, and little (location) privacy to end users. To the best of our knowledge, this work is the first example that the aforementioned disadvantages are not an unavoidable price to be payed for accurate location information in multihop networks.