Marina Ottonello

Cognitive Radios With Multiple Antennas Exploiting Spatial Opportunities

In this correspondence, the achievable rates of the so called “multiple-input multiple-output interference channel,” exploited by a couple of single antenna primary terminals and two antenna cognitive radios under specific interference constraints, are analyzed. In particular, by assuming perfect channel state information at the cognitive terminals, a closed form expression for a linear precoding and linear reception scheme, which guarantees to meet the achievable rates and no mutual interference between primary and cognitive terminals, is obtained. Numerical results regarding the effects of different fading channels and of an imperfect knowledge of the channel are provided to evaluate the performances of the proposed scheme in real environments.

OFDM Recognition Based on Cyclostationary Analysis in an Open Spectrum Scenario

In this paper the problem of detecting the presence of similar OFDM signals, i.e. WLAN and WiMAX signals, in an Open Spectrum scenario is faced. The identification of the channel occupancy and the signal classification are performed by using a fast detector based on a single spectral correlation function estimator and a multi-class support vector machine classifier which are designed and tested in a multipath environment. Finally, the obtained numerical results and the amount of processing necessary to perform the considered operations are reported and discussed.

Distributed Cognitive Sensor Network Approach for Surveillance Applications

The application of intelligent systems composed by smart cameras is continuously spreading in a wide range of applications, playing a key role in public, military and commercial scenarios. As well, in the last years, the capability of Wireless Sensor Networks to collect information from the environment in a distributed manner has been successfully applied in both civilian and military applications. In this paper, basing on recent studies on autonomous cognitive systems, we explore the concepts for designing interactive, adaptable and intelligent multi-sensor surveillance systems able to react to situations in a preventive way by using actuators placed in the monitored environment. To this end, taking inspiration from Ambient Intelligence (AmI) and Cognitive Radio (CR) paradigms, fusion of information provided by heterogeneous sensors is used to improve awareness regarding surrounding environment.

Comparison among Cognitive Radio Architectures for Spectrum Sensing

Recently, the growing success of new wireless applications and services has led to overcrowded licensed bands, inducing the governmental regulatory agencies to consider more flexible strategies to improve the utilization of the radio spectrum. To this end, cognitive radio represents a promising technology since it allows to exploit the unused radio resources. In this context, the spectrum sensing task is one of the most challenging issues faced by a cognitive radio. It consists of an analysis of the radio environment to detect unused resources which can be exploited by cognitive radios. In this paper, three different cognitive radio architectures, namely, stand-alone single antenna, cooperative and multiple antennas, are proposed for spectrum sensing purposes. These architectures implement a relatively fast and reliable signal processing algorithm, based on a feature detection technique and support vector machines, for identifying the transmissions in a given environment. Such architectures are compared in terms of detection and classification performances for two transmission standards, IEEE 802.11a and IEEE 802.16e. A set of numerical simulations have been carried out in a challenging scenario, and the advantages and disadvantages of the proposed architectures are discussed.

Signal classification based on spectral redundancy and neural network ensembles

In the last couple of decades, the introduction of new wireless applications and services, which have to coexist with already deployed ones, is creating problems in the allocation of the unlicensed spectrum. In order to overcome such a problem, by exploiting efficiently the spectral resources, dynamic spectrum access has been proposed. In this context, cognitive radio represents one of the most promising technologies which allows an efficient use of the radio resource by collecting, processing and exploiting information regarding the spectrum utilization in a monitored area. To this end, in this paper the problem of classifying similar signals characterized by different spectral redundancies is addressed by using a neural network ensemble. A set of simulations have been carried out to prove the effectiveness of the considered algorithms and numerical results are reported.

A comparison among cooperative spectrum sensing approaches for cognitive radios

In this paper, a comparison among different cooperative spectrum sensing approaches is provided. It is assumed that the secondary terminals autonomously perform local spectrum sensing and forward their decision to a fusion center. It combines the received data to obtain the global decision, i.e. the presence or the absence of the primary user in the monitored environment. In particular, three fusion rules, i.e. OR, AND and optimal, are compared in terms of required processing capabilities at the fusion center and at the secondary terminals, and required control channel capacity. Numerical simulations in a practical heavy multipath environment are provided to compared the performances of the considered approaches.

Difficulties in Recognizing Ill-Posed Electromagnetic Problems Involving Wrong Effective Models of Media

The set of ill-posed time-harmonic electromagnetic boundary value problems is shown to be much richer than expected so far, when all fine details of composite media are neglected and effective media, possibly anisotropic, are considered. This result seems to suggest that it can be extremely difficult to identify wrong formulations of electromagnetic boundary value problems also because, unfortunately, numerical simulations with common discretizations could give no help in recognizing them.

Antenna systems with embodied cognition for next generation wireless communications

In this contribution, the embodied cognition antenna system has been introduced as a possible approach to design an efficient communication system operating in a wide set of scenarios. Some results obtained in a practical application have been shown.

Performance evaluation of a multiple antenna system for spectrum sensing

In this work, a comparison between the performance of a single antenna and a multiple antenna system which have to identify two similar OFDM signals, is provided. Numerical simulations have shown that multiple antenna systems allow to obtain better performance with respect to single antenna systems with a significant reduction of the observation time, also in multipath environment.

Simple waveguide junctions whose straightforward modelling leads to unsolvable boundary value problems

In this contribution the importance of the a priori evaluation of the well posedness of the models of interest is pointed out. It has been shown that even for trivial models of time-harmonic electromagnetic boundary value problems no solution can exist for infinite many regular and non pathological excitations. For these models, even the very popular technique based on the modal expansion should be considered with care since the series determining the fields in the domain do not converge. Of course, the results obtained by numerical simulators for problems involving one of the above considered dielectric configurations are completely meaningless.