Entropy concept is related to uncertainty and predictability of random time series. The estimated trend of such a parameter can provide useful information and possibly predict future behavior of a number of non-stationary noisy signals. The goal of this paper consists of analyzing the Covid19 signal made by the number of registered infections in Italy during the first four months of the pandemic epidemy (March-June 2020). Finally, some considerations are drawn after matching historical dates of some Covid-19 related Acts made by the Italian Government (i.e., lockdown and unlockdowns). Based on the obtained results, we could conjecture that the provisions have inducted people to a common behavior concerning local mobility during the lockdowns and the progressive unlockdowns of the quarantine period in Italy.

Spectrum sensing (either cooperative or non-cooperative) is the key enabling technology to identify unused (free) frequency bands in dynamic spectrum access contexts. We propose a reputation-based cooperative spectrum sensing method that, improving the sensing performance of self-organizable networks, allows the detection and further rejection of all those malicious users that implement Byzantine attacks. The performances of our method are evaluated in terms of detection probability of the primary user, and in terms of the number of both correctly identified attackers and discarded honest users. The simulation results show the robustness of our method in detecting several kinds of Byzantine attacks, outperforming the (blind and non-blind) conventional approaches.

The effective monitoring of ballasted railway track beds is fundamental for maintaining safe operational conditions of railways and lowering maintenance costs. Railway ballast can be damaged over time by the breakdown of aggregates or by the upward migration of fine clay particles from the foundation, along with capillary water. This may cause critical track settlements. To that effect, early stage detection of fouling is of paramount importance. Within this context, ground penetrating radar (GPR) is a rapid nondestructive testing technique, which is being increasingly used for the assessment and health monitoring of railway track substructures. In this paper, we propose a novel and efficient signal processing approach based on entropy analysis, which was applied to GPR data for the assessment of the railway ballast conditions and the detection of fouling. In order to recreate a real-life scenario within the context of railway structures, four different ballast/pollutant mixes were introduced, ranging from clean to highly fouled ballast. GPR systems equipped with two different antennas, ground-coupled (600 and 1600 MHz) and air-coupled (1000 and 2000 MHz), were used for testing purposes. The proposed methodology aims at rapidly identifying distinctive areas of interest related to fouling, thereby lowering significantly the amount of data to be processed and the time required for specialist data processing. Prominent information on the use of suitable frequencies of investigation from the investigated set, as well as the relevant probability values of detection and false alarm, is provided.

Cognitive radio is establishing itself as the most promising technology in tackling the problem of spectrum scarcity. It allows secondary users to opportunistically access and re-use the spectrum resources under-utilized by licensed or primary users. Spectrum sensing (either cooperative or non-cooperative modes) is exploited to identify those unused (free) frequency bands. This new technology has been proved to be vulnerable to an increasing number of attacks, such as Byzantine attacks. Here, we propose a novel reputation-based cooperative spectrum sensing method that first detects, and then rejects any malicious secondary user, thus improving the system performances. We evaluate the error probabilities (detection vs. false alarms) of the system, as well as the number of both correctly identified attackers and discarded honest users. Finally, we compare our method to a recently published reputation-based method (either blind or non-blind). As shown by the simulation results, the proposed method outperforms the conventional approach, confirming its robustness in detecting different types of Byzantine attacks.

In cognitive radio networks, automatic modulation recognition (AMR) is a fundamental step to perform the classification of different modulation formats. It plays an important role both in military and civil applications. For a cognitive radio receiver, AMR is the intermediate step between signal detection and demodulation. In this work, we propose a novel blind AMR algorithm to distinguish amongst both digital and analog signals. In particular, we exploit higher order moments as well as some features of the received signals, recognizing not only the modulation formats (amplitude, phase, and frequency) but also the levels of the constellations. We can classify up to 17 different (analog and digital) modulations. The simulation results confirm the validity of our approach for blind modulation recognition in cognitive radio applications.

This paper presents an interdisciplinary application of communication services to business. In particular, an extrapolation algorithm for financial trading is here discussed by means of a preliminary case study. We exploit the hidden market trends of historical stock quotes applying signal processing to financial trading. Our case study consists of an example of binary options stock trading. Binary options trading is based on algorithms of financial data processing, that usually run on remote proprietary broker platforms, providing the customer with the proper option to possibly trade a given stock. Here, we have investigated the performance of a simple algorithm which includes one buy / sell order per week. We have analyzed real sets of historical stock quotes, evidencing the asymmetry of achievable economic returns. In fact, the devised signal processing algorithm has denoted a (simulated) overall trading gain in the 82% of cases, showing that engineering management fruitfully applies to financial stock trading.

This work investigates a new code acquisition technique for wireless communications in presence of cell correlation. Code synchronization must be addressed in the most rapid and efficient way: even a small misalignment can cause dramatic signal-to-noise ratio (SNR) degradation. Serial cell search is usually adopted for pseudo noise (PN) code acquisition to reduce the processing complexity in mobile terminals for spread spectrum (SS) communication systems. Unlike the simple case of one (timing) cell per chip, the detection variables between contiguous cells, for sizes less than one chip period, are not independent and possibly strongly correlated. We propose a new test that takes into account several correlated cells at once. Our numerical and simulation results show that our method drastically improves the conventional approach in terms of detection probability, allowing a significant reduction of the mean acquisition time in code synchronization for wireless communications. The performance improvement is obtained with a negligible increasing of the system computational complexity.

In cognitive radio networks, the unoccupied frequency bands licensed to primary users can be opportunistically accessed by secondary (low-power or hidden) cognitive users. Secondary users can be authorized low-power users, or unauthorized (hidden) users that occupy the band illegally transmitting under the noise level. More in details, the devised method is able to detect unknown low-power constant-modulus signals in noise of unknown variance, exploiting higher order moments of the received signal. The decision variable used in the detection stage is represented (only) by the estimated power of the hidden signal. Performance analysis is carried out in comparison with conventional energy detection, in the presence of noise uncertainty. In particular, the detection probabilities of the proposed and conventional methods as well as the mean detection time are evaluated and compared. The numerical results, obtained from wide simulation trials, have evidenced the efficiency of our method for detecting the hidden user's low-power signal in cognitive communications.

This paper addresses the problem of dynamic spectrum access, discussing a new method for spectrum sensing in cognitive radio networks. In particular, an innovative technique for the detection of an OFDM-based primary user signal is here proposed. Performance analysis is carried out in comparison with conventional spectrum sensing method that exploits the autocorrelation coefficients. Unlike the conventional method, our strategy is completely blind and can be applied with no a priori knowledge of any characteristics of the signals of interest. Simulation results have been carried out under operating settings, typical of wireless local area networks.

This work discusses a fast generation procedure of authentication codes, for multimedia content cryptography, whose length (and computational complexity) can be tuned accordingly to the specific mobile application and service. In this work, we propose a digital algorithm to generate a pair of long (asymmetric) keys from one short primitive key. According to our results, the devised procedure provides a watermarking algorithm to hide the authentication information inside the multimedia content (intra-frames of MPEG video streams or JPEG images) with the same robustness of similar previous attempts but with less computational complexity.

This work proposes an effective time-delay estimator for PN satellite signals, exploiting a fast triangular interpolator, running on three estimated ambiguity samples in the neighborhood of the coarse estimate. Performance analysis (theory and simulation) is carried out in comparison with conventional approaches based on the interpolation, usually carried out by (time-consuming) narrow-band over-sampling or (fast) fitting of few samples of a smoothed function of the ambiguity function around its maximum. The theoretical results, substantiated by computer simulations, have evidenced that the devised method outperforms the conventional estimator for all the timing offsets and is well suited for satellite spread-spectrum communications.

This paper addresses the problem of time-delay estimation and proposes an effective time-delay estimator for spread-spectrum communications. The main contribution of our work is twofold: first, we define a new objective function that analytically expresses the performance of different estimation criteria. Second, we introduce a new estimator that outperforms the conventional approaches. In particular, we develop a unified approach, deriving the performance trends of several time-delay estimators by one parametric closed form expression. Furthermore, we propose a new estimator that exploits a fast interpolation, running on few samples in the neighborhood of the coarse estimate, i.e. the (abscissa of the) estimated maximum of the ambiguity function. Mathematical expressions for bias and variance of the estimation error are derived and numerically evaluated by reduced Taylor's expansions up to the second order. The theoretical results, substantiated by computer simulations, have evidenced that the devised method is well suited for spread-spectrum satellite communications.

This contribution proposes an effective procedure for the acquisition of pseudo-noise code in satellite spread-spectrum localization systems. The main contribution of our work is twofold: first, we define a new objective function that is able to exploit the capabilities of different detectors in only one ambiguity function. Then, we introduce a compound detection procedure that, taking advantage of a fast interpolation of the optimum discrete samples, outperforms the conventional approaches. Wide simulation trials have been conducted to evidence that the devised methods are well suited for the incoming spread-spectrum satellite global localization systems.

This letter presents an efficient method for optical code division multiple access (OCDMA) code acquisition based on unipolar optical orthogonal codes. We propose a two-dwell acquisition procedure and provide closed form expressions to analyze the system's error probabilities. Our results match the Multiple Shift (MS) algorithm, recently introduced in the literature, and show that our procedure can achieve the same system performance with a lower computational complexity.

In this work, we derive a blind equalizer that pursues the maximization of an objective function, consisting of the ratio between the square of the mean signal power and the variance of the signal power. The performance of the addressed equalizers is then investigated by focusing on DS/CDMA communication environments in a downlink scenario. In particular, we have evidenced the effectiveness of the presented equalizer in the numerical examples, in terms of robustness against the effect of interference, as well as in terms of convergence rate, in spite of a small amount of extra processing.

This paper addresses the problem of initial synchronization of pseudo-noise code. A new code acquisition technique for spread-spectrum communication systems using band-limited chip waveforms is presented. Unlike conventional power detector based on testing the estimated maximum of the ambiguity function, the devised detector exploits a fast parabolic interpolation, running on three estimated ambiguity samples in the neighborhood of the coarse estimate. Performance analysis is carried out in comparison with conventional detector. Mathematical expressions for the probability of false alarm and detection are derived. They are numerically evaluated, under operating settings, by a reduced Tayloriquests expansion up to the second order. The theoretical results, substantiated by computer simulations, have evidenced that the devised method is well suited for asynchronous spread-spectrum communications. In particular, the acquisition performance depends on the actual offset between the received and the reference code waveforms, which are randomly distributed (in chip-asynchronous systems) within one sampling period. In fact, the parabolic interpolation technique outperforms the conventional detector for a wide range of code offsets because it is able to self-synchronize the testing variable around the true offset.

This paper proposes a business model founded on Bayes decision test for video-call billing. This model is based on the end-to-end Quality of Service (QoS) obtained exploiting the tracing watermarking procedure recently introduced in literature. In particular, we employ the watermark embedded in each transmitted video-sequence to monitor the QoS of the communication link and then to adequately fare the user depending on the real received video-quality. We need to know only the MSE of the received watermark to estimate the end-to-end QoS of the communication link. Numerical results are conducted to characterize the effectiveness of the proposed method, using two different business scenarios, and confirm the validity of such approach. Therefore, the network operator is able to implement an adaptive billing strategy, depending on the effective received quality and maximizing the profit.

This paper presents the problem of identifying whether a received signal at a base station is due to a line-of-sight (LOS) transmission or not (NLOS). This is a first step towards estimating the mobile station's location. We formulate the NLOS identification problem as a binary hypothesis test by exploiting the Rician factor estimation. In particular, results from wireless environments with simulated geometry showed that the new test can decide for a LOS or NLOS condition using a small amount of samples. Therefore, changes from NLOS to LOS propagation can also be tracked quickly. This information is of high significance for location purposes in a wireless cellular network since time-of-arrival (TOA) and time-difference-of-arrival (TDOA) information based on LOS connections can be weighted stronger in a location computing algorithm and hence can lead to higher positioning accuracy. Otherwise, if the connection is identified as NLOS it can be useful to adopt a 2-D signal processing (space-time processing) strategy with an antenna array, instead of using the high complexity of the TOA and TDOA methods.

Tracing watermarking has been recently proposed as a technique to provide a blind measure of the quality of service of the communication link, focusing on multimedia communication scenarios. 3G communication scenarios, where each customer transmits both voice and MPEG-4 video sequences in real time, have been considered. Typical video-phone call consists of close shots of speakers, framing their face in the foreground. For such particular application, a novel colour space (YST) is adopted to minimise the perceptual distortions on face coding introduced by watermarking. In the YST space, the luminance component (Y) is the same as in conventional YUV space, whereas the vectors S and T lie within the chrominance (UV) plane. The S (skin) component is a linear combination of U and V obtained as the ‘average’ chrominance estimated from an assorted set human faces to achieve a reasonable generalisation. The third component, T, is defined as orthogonal to the YS plane. The results show the benefits obtained in digital watermarking by the new representation against the conventional approach. In fact, the sensitivity of the YST representation outperforms the conventional one in terms of objective (mean square error, peak signal-to-noise ratio) and subjective (video-quality metrics) indicators.

A new special function, called the modified generalized Q (MGQ) function, is here defined to analytically express the performance of the pseudonoise code acquisition based on matched filter correlators. In the considered case of two cells per chip, no convergent infinite series have been found in the open literature expressing the probabilities of false alarm and detection. The performance is analyzed in terms of mean acquisition time for signal-to-noise ratios of practical interest

Many studies have shown that color representation is very relevant in image processing and communications techniques. In this contribution, we propose a new color space, based on the "skin" component, in order to minimize the perceptual distortions introduced by digital watermarking. We have therefore defined a new color space, called YST, in which the brightness component is the same of YUV. Conversely, the S (skin) component has been obtained estimating the average values corresponding to a set of different colors of human faces. The criterion for this selection was to achieve a reasonable degree of generalization. The third component, T, is automatically identified by the Gram-Schmidt procedure in order to have an orthogonal color space. Analytical results are used to show the benefits obtained in digital watermarking by the new representation as well as in terms of peak signal-to-noise ratio and video quality metrics.