Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

In this paper, we consider the problem of spectrum sensing by using multiple antenna in cognitive radios when the noise and the primary user signal are assumed as independent complex zero-mean Gaussian random signals. The optimal multiple antenna spectrum sensing detector needs to know the channel gains, noise variance, and primary user signal variance. In practice some or all of these parameters may be unknown, so we derive the generalized likelihood ratio (GLR) detectors under these circumstances. The proposed GLR detector, in which all the parameters are unknown, is a blind and invariant detector with a low computational complexity. We also analytically compute the missed detection and false alarm probabilities for the proposed GLR detectors. The simulation results provide the available traded-off in using multiple antenna techniques for spectrum sensing and illustrates the robustness of the proposed GLR detectors compared to the traditional energy detector when there is some uncertainty in the given noise variance.

Multiple antenna spectrum sensing in cognitive radios

Fundamentals of statistical signal processing: Estimation theory: by Steven M. KAY; Prentice Hall signal processing series; Prentice Hall; Englewood Cliffs, NJ, USA; 1993; xii + 595 pp.; $65; ISBN: 0-13-345711-7

Cognitive users need to detect primary users continuously and rapidly.Cooperative spectrum sensing in cognitive radio(CR) networks is analyzed.Cooperative spectrum sensing in the ideal network with two cognitive users can reduce the mean detection time.Detection probability to primary users can be improved by multi-cooperative users in multi-user networks.Finally,the realization of multi-user networks is considered.

Cooperative Spectrum Sensing in Cognitive Radio Networks

Widely regarded as one of the most promising emerging technologies for driving the future development of wireless communications, cognitive radio has the potential to mitigate the problem of increasing radio spectrum scarcity through dynamic spectrum allocation. Drawing on fundamental elements of information theory, network theory, propagation, optimisation and signal processing, a team of leading experts present a systematic treatment of the core physical and networking principles of cognitive radio and explore key design considerations for the development of new cognitive radio systems. Containing all the underlying principles you need to develop practical applications in cognitive radio, this book is an essential reference for students, researchers and practitioners alike in the field of wireless communications and signal processing.

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Principles Of Cognitive Radio

Radio frequency (RF) fingerprinting techniques have been used as an extra security layer for wireless devices. Unique fingerprints are used to identify wireless devices in order to avoid spoofing or impersonating attacks. These unique features can be extracted from imperfections of analog components during the manufacturing. This paper presents a general review of recent progress on RF fingerprinting techniques. Several studies are investigated for RF fingerprinting using different parts of a signal. The majority of these studies have been focused on the transient part of the signal. For this purpose, the transient signal must be extracted precisely. A number of common techniques of transient extraction are theoretically analyzed in this review. Then, some other approaches using the modulated part of the signal are also discussed. For all these approaches, the applied methodologies, the classification algorithms and a taxonomy of features are described. A comprehensive overview of the methods in RF fingerprinting is presented to demonstrate the state-of-the-art works.

A Review of Radio Frequency Fingerprinting Techniques

Traditionally, the frequency spectrum is licensed to users by government agencies in a fixed manner where the licensee has exclusive right to access the allocated band. However, with increasing demand for the spectrum and scarcity of vacant bands, a spectrum policy reform seems inevitable. Meanwhile, recent measurements suggest the possibility of sharing spectrum among different parties subject to interference-protection constraints. In order to enable access to an unused licensed spectrum, a secondary user has to monitor licensed bands and opportunistically transmit whenever no primary signal is detected. Spectrum-sharing between a primary licensee and a group of secondary users has been studied. The structure of an asymptotically optimum detector based on the measurements of all secondary users is derived and the effect of the quantisation error in such a system is evaluated. Also, it is shown that by using the proposed detector in a sequential detection structure, it is possible to shorten the decision time needed by the detector. The results show the superiority of the proposed detector to other schemes.

Asymptotically optimum detection of primary user in cognitive radio networks

Several target position finding methods are proposed in various papers mainly regarding sensor networks. However, the problem of position finding in passive radar systems is somewhat different from the general case of sensor networks. Generally, in a passive radar system, there are few receivers located at short distances when compared with the it distance from the target. In this case, a problem known as geometric dilution of precision (GDP) occurs, which considerably increases the error of many proposed methods. This phenomenon can even make the position finding equations non-solvable. Regarding this fact, we have developed a least mean square error (LMSE) based method, which uses both the angle of arrival (AOA) and time difference of arrival (TDOA) measurements to estimate almost precisely the position of very distant targets in a passive radar system. A simple equation is derived here to compare the TDOA and AOA accuracies. Then, it is shown that whenever the accuracies of these two measurements are comparable, the proposed method estimates the target position more precisely than the conventional AOA-only and TDOA-only methods. It also avoids the non-convergence behaviour encountered in TDOA-only methods.

Joint time difference of arrival/angle of arrival position finding in passive radar

Automatic dual censoring cell-averaging CFAR detector in non-homogenous environments

Recently, axial displacement detection of transformer winding has been performed using synthetic-aperture radar (SAR) imaging, as an online method, in ultra-wideband frequency band. Another important problem in power transformers is partial discharge (PD), which emits signal in the ultra-high-frequency (UHF) frequency band. If detection of axial displacement using SAR imaging can be applied to the UHF band, both defects can be detected using only one set of antennas and application of these methods can be more economic. However, as shown in this paper, using the same frequency band for detection of both defects leads to wrong conclusions about winding conditions, if PD is occurred during the application of SAR imaging. As a solution, UHF stepped-frequency imaging method and generalized likelihood ratio test method are proposed for detection of axial displacement. Finally, on a three-phase real transformer both defects are simultaneously detected using designed monitoring system.

Yaser Norouzi

Papers

A Review of Radio Frequency Fingerprinting Techniques

Asymptotically optimum detection of primary user in cognitive radio networks

Joint time difference of arrival/angle of arrival position finding in passive radar

Automatic dual censoring cell-averaging CFAR detector in non-homogenous environments

Feasibility Study on Simultaneous Detection of Partial Discharge and Axial Displacement of HV Transformer Winding Using Electromagnetic Waves