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Cognitive radio (CR) is currently one of the most promising solutions for designing spectrum-efficient wireless com- munication systems. In this paper, we present a greedy cognitive access policy that handles spectrum sensing with the tools of image processing. By means of the Wigner-Ville transform (WVT), we are able to analyze the time and frequency features of the received interference, and represent them on a time-frequency grid as an image in which brightness reveals the spectrum occupancy. Ac- cording to sensed interference, each secondary user autonomously tries to access the grid following a multiple-division principle, i.e., by properly shaping the signal in the code, time, and frequency domains. In detail, this is realized by processing the WVT to derive the shaping mask (and the matching algorithm) that allows the filling up of the "time spectrum holes." Numerical simulations and a test-bed implementation show how the proposed scheme outper- forms selected state-of-the-art approaches while still presenting an affordable computational cost. Index Terms—Cognitive radio (CR), edge detection (ED), multiple access, Wigner-Ville transform (WVT). I. INTRODUCTION developed here fully embraces the cognitive paradigm and, following (3), is characterized by awareness (through interfer- ence shape detection), the ability to make decisions (shaping is based on the learning/acquisition phases), adaptivity (to con- dition evolutions), reliability (i.e., robustness to impairments), and efficiency (from smart energy consumption). A possible application of this kind of device ranges from medical body area networks (MBANs) or smart grids (not power-lined) to public safety networks. Establishing a connection easily is the common denominator of these networks. In fact, smart grids allow the connection of new devices in an unlicensed band (e.g., electrical vehicles needing to be charged). In the area of public safety, CR was identified in 2008 by both a National Emergency Communications Plan report and the National Broadband Plan (4) as one of the emerging technologies for increasing effi- ciency and effectiveness of spectrum usage. Finally, MBANs need devices able to work in some spectrum bands subject to constraints related to forbidden bands, as specified by different hospitals. In this regard, flexibility and self-configuring ability are two relevant issues. The proposed approach answers those requests.

In this paper, we address the problem of location parameter estimation via a Generalized Method of Moments (GMM) approach. The general framework for the GMM estimation requires the minimization of a suitable, generally nonconvex, elliptic norm. Here we show that, if the estimandum is a shift parameter for a suitable statistic of the observations, a fast, DFT-based, computationally efficient procedure can be employed to perform the estimation. Besides we discuss the relation between the GMM estimation and the maximum likelihood (ML) estimation, showing that the GMM estimation rule provides a closed form ML estimator for shift parameters when the observations are multinomially distributed. As a case study, we analyze a GMM blind phase offset estimator for general quadrature amplitude modulation constellations. Simulation results and theoretical performance analysis show that the GMM estimator outperforms selected state of the art estimators, approaching the Cramer-Rao lower bound for a wide range of signal-to-noise ratio values.

This paper introduces a novel, not data aided, phase-offset estimator for quadrature amplitude modulated (QAM) signals. Contrarily to near-efficient existing phase acquisition techniques, this estimator does not require a preliminary gain adjustment stage while its accuracy preserves the slope of Cramer-Rao bound for medium-high signal-to-noise ratio (SNR) ranges, where it typically outperforms existing blind estimators, with significant improvement for dense and cross QAM constellations. Moreover, it needs only a very rough estimate of the SNR. Like other gain-control-free blind phase-offset estimators, it measures the amount of the cyclic shift by which the (four-folded) phase probability density function (pdf) is rotated under an unknown phase-offset. Estimation of the phase-offset-induced cyclic shift is conducted first by measuring the received data phase pdf by a canonical phase histogram procedure, then by estimating the phase-offset-induced cyclic shift through a cyclic cross correlation-based procedure between the measured phase histogram and a reference phase pdf evaluated within the zero phase-offset hypothesis. Actually, the estimation procedure is presented in a generalized version that considers a tomographic projection of the bidimensional (magnitude/phase) pdf of suitable nonlinear transformations of the received data. The tomographic projection performs a magnitude weighing on the pdf, and this, in turn, results in an improved overall estimation accuracy, as shown by theoretical analysis and numerical simulations here performed to assess the estimator performance.

The ever increasing need to be able to take advantage of broadband services without the need to increase the electromagnetic pollution, has led the scientific community, in recent years, to look for alternatives to the use of a radio frequency communication. From this, it stems the need of budding paradigm of visible light communications. In the context of the activities of the IEEE 802.15.7 Task Group, a new modulation format named Color Shift Keying (CSK), based on sending signals spaced in the domain of the wavelength able to both support the communication and the illumination of indoor environments has been tackled. In this paper, a transmission scheme based on the use of the CSK modulation which also makes use of a modulation format that descends from the Pulse Position Modulation (PPM) has been proposed. The aim of this contribution is also proposing the receiver architecture for that kind of transmission and then evaluate its performance in terms of Bit Error Rate (BER) of Transmission Rate by performing also comparisons with the literature. The proposed scheme is robust with respect to optical interference and presents high rate and low BER at the cost of a bit complexity increasing with respect to other approaches.

The need for underwater reliable connections requested to provide different services as sea monitoring, devices control and camera images/videos may lead to require also large rate values. Due to the very limited bandwidth achieving few Khz, space diversity techniques can aid in this twofold mission. In this paper we investigate the use of an underwater acoustic MIMO technique, and jointly adopt the Pulse Position Modulation (PPM), in order to improve the data rates without reducing the reliability of the link. PPM is known to be power efficient modulation format while it is bandwidth inefficient so the use of MIMO can compensate that drawback with reasonable complexity. The performance has been evaluated on the basis of signal recordings for what concerns interference.

In this paper we investigate how to rephrase the concepts of cognitive access, originally developed for radio communications, in the framework of underwater acoustic communications. Differently from classical cognitive radio access, where each signal at the receiver is generated by a communication source, in the underwater scenario acoustic signals at the general receive node are likely to be due to communication source as well as natural/artificial acoustic sources (e.g mammals, ship engines and so forth). In order to maximize the access probability for cognitive acoustic nodes, we then focus on understanding the nature of the sensed interference via the tools of image classification, being the image the spectrogram of the acquired signal.

The goal of this chapter is twofold. Firstly, we provide the reader with a summary of the state-of-the-art depth map interpolation techniques. Secondly, we present recent results making use of markovian priors for depth map interpolation. Specifically, we provide insight into Markovian mathematical models recently presented in the literature, and we show that such priors allow interpolation without making use of contemporaneously acquired luminance views. This feature extends the scope of the interpolation procedure and decouple its performances from those of the luminance/depth images registration stage.

The passive radar uses opportunistic illuminators, such as FM radio or TV transmitters, cellular telephone base stations, etc., to detect and track moving targets. Due to the fact that the radar itself does not transmit any power, it is undetectable. The other advantages of passive radar include its low power consumption, low cost and potential ability to detect stealth targets, due to the multistatic geometry and low frequencies used as weel as, it reduces electromagnetic pollution. This paper tackles with the problem of detecting targets close to the coastal and present on the sea surface by using opportunistic signals as The receiving operations aim at detecting the possible presence of reflective objects by stressing the diversity properties of the multiple-input multiple-output configuration due to multiple transmissions related to different communication services.

Vehicle to Infrastructure (V2I) networks can help managing different on-the-road applications and services, especially where the vehicles population is low and Internet access is needed for messaging, alerts, entertainment. Accessing a network through a proper technology requires the possibility of establishing connections with a minimum quality level; besides, a mechanism for switching from a network with poor performance to a better one by means of a so-called Vertical HandOver (VHO) may result of paramount importance. In this work we propose a switching mechanism based on sensing and processing of some physical/access/networking parameters in order to choose the technologies allowing the minimization of outages.

In compressive sensing, the Restricted Isometry Property is an analytical condition on the measurement matrix that assures reconstruction of a signal which is sparse either in the spatial or in a transformed domain given an undersampled measurements' set. In this paper, we demonstrate the RIP for a sparse, structured measurements matrix, referred to as Radon-like CS matrix. The sparse Radon-Like CS matrix favorably applies to real sensing problems, since it significantly reduces the energy/bandwidth cost of actually collecting each and every sensed values contributing to the CS measurements. Simulation results confirm the feasibility of field reconstruction from undersampled CS measurements set obtained using the Radon-Like CS matrix.

UnderWater Acoustic (UWA) channels are narrow bandwidth and typically affected by some interference due to propagation, Doppler effect, noise and possible disturbing signals originated by different acoustic sources. Orthogonal Frequency Division Modulation (OFDM) is an effective answer to such impairments. Resource management in the framework of OFDM usually makes use of channel knowledge without taking care of its cost. This work tackles with the dualism between channel estimation and channel prediction and its impact on adaptive modulation, both from a bandwidth and power point of view also in the presence of acoustic interference. The main result is that adaptivity is worth even if requires some processing both at the transmit and receive sides.

Cognitive access is growing in importance in radio frequency wireless applications for occupying spectrum holes leaved free by licensed and unlicensed primary services. Recently the cognitive paradigm involved underwater communications aspects since this propagation scenario is, generally, rich of acoustic sources. This justifies the curiosity of the scientific community to investigate the possibility of using some of the concept borrowed by the cognitive paradigm. Specifically, we consider an underwater active sensor network where each cognitive node applies a Wigner-Ville image processing based pattern analysis procedure not only for evaluating the presence of interference but also its nature. In fact, if the source of interference is a network node, coexistence issues should be taken into account, while, when the interference source is external (mammals, bubbles or ship engines), in principle the transmission is possible in the interfered bands, provided the presence of the interference does not affect the overall transmission quality.

Wireless sensor networks (WSN), i.e. networks of autonomous, wireless sensing nodes spatially deployed over a geographical area, are often faced with acquisition of spatially sparse fields. In this paper, we present a novel bandwidth/energy efficient CS scheme for acquisition of spatially sparse fields in a WSN. The paper contribution is twofold. Firstly, we introduce a sparse, structured CS matrix and we analytically show that it allows accurate reconstruction of bidimensional spatially sparse signals, such as those occurring in several surveillance application. Secondly, we analytically evaluate the energy and bandwidth consumption of our CS scheme when it is applied to data acquisition in a WSN. Numerical results demonstrate that our CS scheme achieves significant energy and bandwidth savings wrt state-of-the-art approaches when employed for sensing a spatially sparse field by means of a WSN., Comment: Submitted to EURASIP Journal on Advances in Signal Processing

This paper introduces a compressive sampling (CS) scheme for pulse stream images. We adopt a particular sparse sampling matrix, that we call Radon-like CS matrix. Whilst the Radon transform evaluates projections of a given image along different directions, the Radon-like CS matrix evaluates randomly weighted projections of the image along a few directions. We demonstrate that the such CS measurements are invertible and assess the reconstruction accuracy of CS with the Radonlike sampling matrix by numerical trials. The Radon-like CS performs almost as well as state of the art techniques, with a reduced number of operations. As an application example, we show that, when implemented in a resource limited framework such as a Smart Sensors Grid, the sampling matrix significantly reduces inter-node signaling and then the associated energy consumption.

Mobile video streaming services are challenging, as they obey several system constraints, such as random access facilities, efficient server storage, and flexible rate adaptation. Rate adaptation can be performed by means of seamless switching among different encoded bitstreams. The H.264 video coding standard explicitly supports bitstream switching using specific frame coding modes, namely switching pictures (SP). Locations of SP frames affect the overall bit rate and quality of streamed video. In this study, we address the issue of optimal joint selection of the SP frames locations and bit budget allocation at frame layer. The optimization is carried out via a game theoretic approach under assigned system constraints on the overall streaming rate and the maximum random access delay. Numerical simulations show that our frame layer optimal encoding procedure brings advantages in terms of several characteristics of the streamed video, encompassing enhanced rate-distortion, reduced transmission buffer occupancy, equalization of the transmission delays, and more efficient switching.

We introduce a novel, both gain and signal-to-noise ratio independent, constellation unaware, blind frequency offset estimation procedure for QAM signals. Asymptotic performance analysis and numerical simulations show that the herein presented method outperforms a selected state of the art blind constellation unaware estimator, especially for cross constellations.

Power Line Communications (PLC) are one of the most recent technologies proposed to allow the InHome Internet access, in competition with different Wireless Standards as Wi-Fi. The advantages offered by PLC deal with network availability since each modem connected to the plug is able, in principle, to access the Internet while in the Wi-Fi scenario, the propagation environment strongly influences the received signal strength and consequently connection performance. The conventional approach followed in planning the physical layer of PLC systems, like for example in HomePlug solution, is based on Orthogonal Frequency Division Multiplexing (OFDM), able to combat the frequency selective nature of the channel frequency response. However, OFDM presents some drawbacks as, for example, Peak to Average Power Ratio (PAPR) and Inter Carrier Interference (ICI) while a different approach based on constrained signal shaping (single carrier) can solve these problems. In this direction, this work shows a frequency shaping approach where the frequency occupancy is minimized through constraints on spectral emission and link quality level.

The problem of image restoration is considered, where the goal is to recover the original image starting from its blurred and noisy degraded version. A Bayesian restoration procedure is introduced based on modeling the image given the measurements as a Markov Random Fields characterized by spatially variant local priors. A suitable complex valued line process is introduced, generalizing previous literature works, to account for both the intensity and the orientation of image edges. The presence and the orientation of image edges are locally estimated by a computationally efficient filtering stage especially tuned to visually relevant image features, namely a first-order Circular Harmonic Function filter. Simulation results shows the effectiveness of the complex line process in describing local image discontinuities.