A modern interdisciplinary analysis of social networks implies detecting and investigating relevant socio-psychological linguistic markers that carry insight on the nature and characteristics of the social discourse. Associating markers to specific words is a further important step, allowing for an even richer interpretation. By taking as a working example the social discourse in Twitter, we propose a scalable method called PageRank-like marker projection (PLMP) following a rationale inspired by PageRank to fully exploit the interdependencies in a semantic network, so as to meaningfully project markers from a social discourse level (tweets) to its semantic elements (words). The effectiveness of PLMP is shown with an application example on calls to online collective action.

In this work, we tackle the energy consumption problem of edge computing technology looking at two key aspects: (i) reducing the energy burden of modern edge computing facilities to the power grid and (ii) distributing the user-generated computing load within the edge while meeting computing deadlines and achieving network level benefits (server load balancingvsconsolidation and reduction of transmission costs). In the considered setup, edge servers are co-located with the base stations of a mobile network. Renewable energy sources are available to power base stations and servers, and users generate workload that is to be processed within certain deadlines. We propose a predictive, online and distributed algorithm for the scheduling of computing jobs that attains objectives (i) and (ii). The algorithm achieves fast convergence, leading to an energy efficient use of edge computing facilities, and obtains in the best case a reduction of 50% in the amount of renewable energy that is sold to the power grid by heuristic policies and that is, in turn, used at the network edge for processing.

In this paper, we provide new compact integral expressions and associated simple asymptotic approximations for converse and achievability bounds in the finite blocklength regime. The chosen converse and random coding union bounds were taken from the recent work of Polyanskyi-Poor-Verdù, and are investigated under parallel AWGN channels, the AWGN channel, the BI-AWGN channel, and the BSC. The technique we use, which is a generalization of some recent results available from the literature, is to map the probabilities of interest into a Laplace integral, and then solve (or approximate) the integral by use of a steepest descent technique. The proposed results are particularly useful for short packet lengths, where the normal approximation may provide unreliable results.

A tight converse bound to the channel coding rate in the finite block-length regime and under additive white Gaussian noise conditions was recently proposed by Polyanskiy-Poor-Verdú (PPV). The bound is a generalization of a number of other classical results, and it was also claimed to be equivalent to Shannon's 1959 cone packing bound. In this paper, we investigate methods for a reliable numerical evaluation of the bound, which is troublesome even for not too large values of the block-length n, by compactly expressing the Polyanskiy, Poor, and Verdú (PPV) converse bound in terms of non-central chi-squared distributions, and by evaluating those through an integral expression and a corresponding series expansion which exploit a method proposed by Temme. As a result, a robust evaluation method and new insights on the bound's asymptotics, as well as new approximate expressions, are obtained.

The efficient management of the supply and demand in electricity networks is becoming a pivotal issue with important fallbacks both in the technological and financial domains. An interesting topic in this domain is the use of large batteries at the end users premises to reduce the average cost of energy supply, by storing energy when its cost is low and releasing it when the cost is high. In this paper, we wish to gain insights on the impact of some system model parameters, such as battery capacity, charge/discharge rate, power request process, and cost functions, on the cost saving that can be achieved by some selected energy storage algorithms. The study shows that the battery capacity has a direct and rather linear impact on cost reduction, while the effect of charge/discharge rates is less straightforward to predict. Furthermore, we show that, with piecewise, convex and non-decreasing cost functions, the optimal energy storage strategy has a threshold structure, where the number of thresholds depend on the shape of the cost function and the constraints of the battery.

The alternating direction multiplier method (ADMM) was originally devised as an iterative method for solving convex minimization problems by means of parallelization, and was recently used for distributed processing. This letter proposes a modification of state-of-the-art ADMM formulations in order to obtain a scalable version, well suited for a wide range of applications such as cooperative localization and smart grid optimizations. The resulting algorithm is distributed and scalable, it assures fast convergence speed and robustness to errors. Its performance is tested with an application example based upon cooperative localization.

In this paper, a consensus-based clock synchronization algorithm is presented and its resilience to frequency displacement estimation errors as well as communication noise is analyzed. The synchronization-enforcing control that is to be applied to clock periods is derived upon re-casting the consensus problem into a convex optimization problem and solving it in a distributed fashion via alternating direction method of multipliers. Conversely, plain consensus is used for reaching agreement on clock values. The proposed algorithm achieves higher convergence rates and equivalent noise resilience with respect to algorithmic solutions based on the only plain average consensus. The superior clock synchronization performance is corroborated via numerical tests.

This paper deals with the spectral analysis of multi-h continuous phase modulation (CPM) signals. A new solution to the problem is obtained by identifying an inner hidden Markov model in the CPM signal, which can be accomplished by expressing the modulator as the cascade of a sequential machine (SM), and a bank of PAM modulators. An in-depth study of the resulting Markov chain shows that it is both cyclostationary and reducible, and proper tools are identified to address these peculiarities. As a result, the multi-h CPM spectrum is expressed as a combination of Fourier transforms of portions of a CPM signal, thus allowing an efficient numerical evaluation through fast Fourier transforms (FFTs).

This paper presents a time hopping ultra wide band (TH-UWB) receiver design targeted to high performance and low complexity. The classical Schmidl and Cox idea of extracting the frequency offset from the phase of a correlation measure between two identical transmitted signals is here extended to a TH format. The algorithm exploits the low duty cycle of the time hopping access, and combines received samples in order to strengthen the signal-to-noise ratio. A clever selection of which samples to use in the correlation measure (first and last third of the received signal) is proved to perform 0.5 dB from the Cramer-Rao lower bound, thus providing an improvement of 0.75 dB with respect to the standard approach of the literature (correlating the first and second halves of the received signal). A modified algorithm that suitably weights received samples is also proposed for achieving robustness in impulsive multiple user access scenarios.

Frequency offset estimation for time-hopping (TH) ultra-wide-band (UWB) is addressed in the literature by relying on an AWGN assumption and by exploiting a periodic preamble appended to each packet. In this paper we generalize these techniques with two aims. First, we identify a solution which does not rely on any periodic structure, but can be implemented with a generic TH format. Second, we identify a solution which is robust to multiple access interference (MAI) by assuming a Gaussian mixture (GM) model for MAI. In fact, GMs have recently been identified as good descriptors of UWB interference, and they provide closed form and limited complexity results. With these ideas in mind, we build a data aided maximum likelihood (ML) estimator. The proposed ML solution shows quasi optimum performance in the Cramer-Rao bound sense, and proves to be robust in meaningful multiple user scenarios.

This paper describes the design of several simple IR-UWB receivers that could be used for sensor networks. The research is looking for a simple design with low complexity and good performances. To achieve this, a priori information is needed: the statistical knowledge of the Multi User Interference (MUI). In many systems the Gaussian distribution is a common presumption but due to the impulsive nature of the interference, in the Impulse Radio Ultra Wide Band (IR-UWB) systems this presumption is no longer possible to characterize MUI. We investigate here the use of mixtures of Gaussian, Laplacian, and generalized Gaussian random variables to model the MUI.

We propose two new receiver architectures for a ultra wide band (UWB) system based on the IEEE 802.15.4a standard. The design objective is robustness against strong multiple access interference (MAI). The first proposed structure models MAI as an additive white Gaussian noise (AWGN) whose power is estimated at each frame, rather than on average, in such a way to take account of the impulsive nature of interference. The second approach aims at jointly optimizing demodulation and decoding, and, in this case, MAI is modeled as a generalized Gaussian mixture process. In both cases, the maximum likelihood receiver is derived. Numerical results in a IEEE 802.15.4a scenario show that the AWGN receiver with local power estimate provides a performance comparable to the best existing techniques, while requiring a much lower computational complexity. The joint optimization of demodulation and decoding provides a further gain, especially at low packet error rates, at the cost of an additional signal processing effort. Still, low complexity solutions holding the performance gap are identified in this latter class.

We design new receiver structures suited for the ultra wide band (UWB) standard IEEE 802.15.4a. The design objective is a receiver robust to multiuser access interference (MAI), which is a particular severe impairment in simple wireless personal area networks (W-PAN). Unlike most approaches of the literature that focus on the optimisation of decoding, we jointly optimize both demodulation and decoding, deriving new maximum likelihood (ML) schemes with enhanced capabilities in MAI rejection. In particular, a generalized Gaussian mixture model is assumed for the description of MAI, which includes as sub-cases the Gaussian and Laplacian models but has the potential to describe much more general scenarios. Simulations carried out on the IEEE 802.15.4a standard and including channel estimation show that the proposed approach significantly outperforms existing solutions in various channel and interference scenarios.

Gaussian mixture (GM) receivers have been recently introduced in the context of ultra wide band (UWB) impulse radio (IR) as a robust alternative to commonly employed techniques. By statistically modeling interference as a GM, as opposed to the ordinary AWGN assumption, such receivers are able to mitigate the effect of multiple user interference (MAI). However, this is achieved at the cost of an increased complexity, commonly thought as an high complexity. In this paper we prove that a suitable reformulation of the GM approach leads to a receiver which is low complexity, while providing the same performance of standard GM. Hence, the GM paradigm is a usable, and welcome, technique for IR applications.

One of the main problems in ultra wide band (UWB) impulse radio (IR) systems is the need to cope efficiently with multiple access interference (MAI). As outlined recently in the literature, this can be achieved by modeling MAI as a Gaussian mixture (GM) random process and deriving the receiver in accordance with a maximum likelihood paradigm. Depending on the chosen context, both rake and chip-matched solutions can be identified. In this paper we compare different solutions, generalize them to a QAM context, and investigate their implementation complexity and robustness to impulsive interference. We also investigate efficient methods to lower the computational demand.

Ultra wide band (UWB) impulse radio (IR) technology calls for robust and low-complexity receiver techniques. State-of-the-art proposals are both coherent ML receivers, noncoherent transmitted reference systems, or hybrid choices, all of which are derived from an AWGN model. In this paper we investigate an alternative technique which has been recently proposed, and which is based upon a Gaussian mixture (GM) model for multiple access interference. We show that this technique exhibits superior performance in comparison to AWGN receivers, and can be implemented with low-complexity.

One of the main concerns in ultra wide band (UWB) impulse radio (IR) technology is the presence of severe multiple access interference (MAI). Efficient receivers should therefore be capable of deleting, or at least mitigating, this effect. Based on the observation that MAI has an impulsive structure, we model it as a Gaussian mixture random process, to derive the optimum receiver accordingly. By carefully simplifying parts of the resulting algorithm, we are able to propose a receiver approach which is efficient in mitigating MAI, while having low computational complexity. Its effectiveness is compared to state of the art approaches by simulations in a realistic scenario.

In this letter, we derive the capacity of ultra-wideband impulse radio (IR) systems employing optimal single-user reception. The environment in which the evaluation is set is that of a dense multipath and equal energy levels for interfering users, where multiple-access interference can be modeled as Gaussian. The investigation covers both binary and M-ary pulse position modulation approaches, employing either hard or soft decoding, and is targeted to low-signal-to-noise ratio/low-power environments where IR is supposed to work.

Recently, innovative multicarrier schemes have been proposed that exploit the transmission of chirp-shaped waves e/sup -j2/spl pi/ct2/ by optimally choosing the chirp parameter c on the basis of the channel characteristics and are more robust to time-varying channels than ordinary OFDM schemes. This concept was applied to continuous-time and to discrete-time systems. In the present paper, we aim at developing those ideas using the affine Fourier transform (AFT), which is a very general formulation of chirp transforms. We present a multicarrier modulation based upon the discrete form of the AFT that is therefore inherently discrete and strictly invertible. Moreover, it allows to define a circular prefix concept that is coherent with the chirp nature of the transmission. The system can be efficiently implemented by adding a simple phase-correction block to standard OFDM modulators/demodulators and can effectively combat interchannel interference when the propagation channel is made of few multipath components affected by independent frequency offsets. Our discrete-time multicarrier scheme is an improved version of Martone's approach (as we also show by simulation results), and exhibits analogous characteristics to Barbarossa's continuous-time system.

This paper presents the investigation carried out for the MetaVision project in the area of lossless compression for digital cinema. The goal of this investigation was to identify, among the many approaches, the one that is most suited to the MetaVision requirements. An extensive simulation campaign has thus identified JPEG-2000 as the best compromise between efficiency, standardization and lossy-to-lossless performance. This result was hardly predictable, especially because of the peculiar kind of material to be coded.

This paper presents a closed-form spectral evaluation of the family of digital pulse interval modulation (DPIM) schemes, where the information is contained in the relative distance between successive pulses. The framework for spectral evaluation is that of stationary symbol sequences derived from variable-length word sequences, which considers the issue of stationarization, a preliminary task to spectral analysis. For all the considered modulation schemes, the spectrum turns out to be a rational function of exp(j2/spl pi/fT), where T is the slot duration. Moreover, spectral lines occur at integer multiples of 1/T, but occasionally may also occur at submultiples of 1/T.