1,721,007 research outputs found
A distributed approach to mode identification and spectrum monitoring for cognitive radios
No full textIn this paper a distributed approach to mode identification and spectrum monitoring is studied. A Wireless Network composed by Cognitive Terminals is used to classify air interfaces present in the radio scene. The use of cooperative strategies and an advanced signal processing tool, Time Frequency analysis, allows to improve the radio awareness of device. Results in the terms of error probability, modeling the probability density function of considered features as Asymmetric Generalized and Generalized Gaussian functions, are compared to error rate showing good performance and coherence of theoretical model with experimental results
Video-radio fusion approach for target tracking in smart spaces
No full textSmart Spaces are an emerging technology which is gathering interest in several domains of application since they allow to supply services and to interact with users in a pervasive way. One of their basic tasks regards the localization of the users in order to provide services in a personalized and location- based way. However since the guarded area is usually complex (e.g. with occlusions) and extent several sensors must be used. In this work video data acquired by video-cameras and radio signals of the WLAN, by which user can access to services, are jointly employed to improve the association between video track and radio identifier, and, through a two step temporal filtering, it is possible to enhance the system reliability. Results are presented in a simulated environment showing the effectiveness of the proposed approach
"Integration Between Navigation and Data-Transmission Systems in a Software Defined Radio Framework"
No full textIn the last years, an increasing interest of the market in devices able to integrate navigation and com-munication technologies has been noticed. Software Defined Radio technology helps in a tight integration of all possible radio signals into one, completely reconfigurable, universal device. In this work the problem of integration of Galileo, Satellite UMTS (S-UMTS) and IEEE 802.11b local wireless LAN has been faced through the usage of a multi-stage super-heterodyne analog front-end able to overlap the different signals into a reduced bandwidth. In this way it is possible the usage of low-cost components both for the analog heterodyne front and for the A/D Converter
"A New Fine Tracking Algorithm for Binary Offset Carrier Modulated Signals"
No full textIn this paper, an analysis of a new synchronization technique for Binary Offset Carrier (BOC) modulated signals will be presented. Goal of the proposed method is to improve the synchronization performances by reducing the synchronization errors due to the characteristic BOC cross-correlation function. The synchronization is generally based on the envelope of the cross-correlation between the received signal and the local replicas. In a classical NRZ modulation this envelope is approximately a triangle whose peak corresponds to the perfect synchronization between the incoming signal and local replicas. In the BOC case, instead, the cross-correlation is given by a set of triangles with positive and negative peaks in which only the central one corresponds to the perfect synchronization. This paper will describe a novel technique characterized by a different choice of the local replica. In this manner the cross-correlation envelope is composed by different triangles with positive and negative peaks; this envelope has one and only one zero-crossing that corresponds to the perfect synchronization. In order to demonstrate the effectiveness of the method, a theoretical analysis has been carried on together with computer simulations. In particular, the main properties of the technique, compared with the classical situation, will be presented
"Neural networks based approach for data fusion in multi-frequency navigation receivers"
No full textIn this paper a novel method to solve the fine synchronization problem in GNSS receivers is presented, The GPS system modernization phase and the Galileo system development will increase signal availability and hence GNSS system-based applications. This variety of uses pervades almost every aspect of GNSS activity and provides the stimulus for its future improvement. For all these causes, in the past few years, there has been a growing interest in the research on the development of techniques and methods for improving the signal reception. Unfortunately, the receiver measurement is usually affected by errors. As already said, in an urban environment the major error source is given by muttipath fading. The proposed method is based on frequency diversity, i.e. the distortions introduced by the channel can be considered different and uncorrelated for sufficiently spaced frequencies. For this reason it is possible to design receivers that, through the usage of multiple frequencies, can improve the reception of SIS, minimizing the distortion effects of the multipath channel. In the proposed system two frequencies in E band, i.e. E5A and E5B, have been considered, and the derived information is fused by using a Neural Network (NN). The NN bases its adaptive fusion on parameters which represent the amount of noise in each of the considered frequencies. Considering the receiver from an higher level, it would be more accurate and efficient if it would be provided by an artificial intelligence that can be developed within the framework of Cognitive Radio devices, the future paradigm for mobile navigation and communication terminals
HOS-based mode classification for infomobility framework
No full textThe growing number of new emerging wireless standards is creating regulatory problems in allocating the unlicensed frequencies. A possible solution for increasing the frequency reusage within the framework of info-mobility cellular systems is the joint exploitation of Smart Antennas and Cognitive Radio. Inside this framework a key-role is played by Mode Identification and Spectrum monitoring algorithms, useful to provide awareness about the channel conditions. In the paper a Mode Identification algorithm, based on the extraction of higher order statistics from frequency distribution of the involved communication modalities and multiple support vector machine classifiers, for a Cognitive Base Transceiver Station is presented. Simulated results, obtained in a simplified framework, will prove the effectiveness of the proposed approach
"A hierarchical Neural Network-based receiver for GNSS systems"
No full textIn this paper a novel method to solve the fine synchronization problem in GNSS receivers is presented. In particular a hierarchical neural network-based solution, able to estimate the channel in which the receiver operates, will be shown. The proposed method is based on two different Neural Networks and it is able to improve the fine tracking performances in urban environment. The solution takes advantage of the Self Organizing Map (SOM) properties, a particular type of Neural Networks useful in unsupervised systems, to improve the performances in presence of multipath
“A distributed wireless sensor network for radio scene analysis”
No full textIn this paper a distributed approach to mode identification is considered.
A Wireless Sensor Network composed by Software De-
fined and Cognitive terminals is used to classify air interfaces present
in the radio scene. Two modes, namely Frequency Hopping Code
Division Multiple Access and Direct Sequence Code Division Multiple
Access, are identified employing a signal processing technique,
Time Frequency analysis, and distributed decision theory.
Results in the terms of error probability are obtained, modeling the
probability density function of considered features as Asymmetric
Generalized and Generalized Gaussian functions
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