On Random Sampling for Compliance Monitoring in Opportunistic Spectrum Access Networks

In the expanding spectrum marketplace, there has been a long term evolution towards more market€“oriented mechanisms, such as Opportunistic Spectrum Access (OSA), enabled through Cognitive Radio (CR) technology. However, the potential of CR technologies to revolutionize wireless communications, also introduces challenges based upon the potentially non€“deterministic CR behaviour in the Electrospace. While establishing and enforcing compliance to spectrum etiquette rules are essential to realization of successful OSA networks in the future, there has only been recent increased research activity into enforcement. This dissertation presents novel work on the spectrum monitoring aspect, which is crucial to effective enforcement of OSA. An overview of the challenges faced by current compliance monitoring methods is first presented. A framework is then proposed for the use of random spectral sampling techniques to reduce data collection complexity in wideband sensing scenarios. This approach is recommended as an alternative to Compressed Sensing (CS) techniques for wideband spectral occupancy estimation, which may be difficult to utilize in many practical congested scenarios where compliance monitoring is required. Next, a low€“cost computational approach to online randomized temporal sensing deployment is presented for characterization of temporal spectrum occupancy in cognitive radio scenarios. The random sensing approach is demonstrated and its performance is compared to CS€“based approach for occupancy estimation. A novel frame€“based sampling inversion technique is then presented for cases when it is necessary to track the temporal behaviour of individual CRs or CR networks. Parameters from randomly sampled Physical Layer Convergence Protocol (PLCP) data frames are used to reconstruct occupancy statistics, taking account of missed frames due to sampling design, sensor limitations and frame errors. Finally, investigations into the use of distributed and mobile spectrum sensing to collect spatial diversity to improve the above techniques are presented, for several common monitoring tasks in spectrum enforcement. Specifically, focus is upon techniques for achieving consensus in dynamic topologies such as in mobile sensing scenarios

Independent component analysis applications in CDMA systems

Thesis (Master)--Izmir Institute of Technology, Electronics and Communication Engineering, Izmir, 2004Includes bibliographical references (leaves: 56)Text in English; Abstract: Turkish and Englishxi, 96 leavesBlind source separation (BSS) methods, independent component analysis (ICA) and independent factor analysis (IFA) are used for detecting the signal coming to a mobile user which is subject to multiple access interference in a CDMA downlink communication. When CDMA models are studied for different channel characteristics, it is seen that they are similar with BSS/ICA models. It is also showed that if ICA is applied to these CDMA models, desired user.s signal can be estimated successfully without channel information and other users. code sequences. ICA detector is compared with matched filter detector and other conventional detectors using simulation results and it is seen that ICA has some advantages over the other methods.The other BSS method, IFA is applied to basic CDMA downlink model. Since IFA has some convergence and speed problems when the number of sources is large, firstly basic CDMA model with ideal channel assumption is used in IFA application.With simulation of ideal CDMA channel, IFA is compared with ICA and matched filter.Furthermore, Pearson System-based ICA (PS-ICA) method is used forestimating non-Gaussian multipath fading channel coefficients. Considering some fading channel measurements showing that the fading channel coefficients may have an impulsive nature, these coefficients are modeled with an -stable distribution whose shape parameter takes values close to 2 which makes the distributions slightly impulsive. Simulation results are obtained to compare PS-ICA with classical ICA.Also IFA is applied to the single path CDMA downlink model to estimate fading channel by using the advantage of IFA which is the capability to estimate sources with wide class of distributions

Resilient Peer-to-Peer Ranging using Narrowband High-Performance Software-Defined Radios for Mission-Critical Applications

There has been a growing need for resilient positioning for numerous applications of the military and emergency services that routinely conduct operations that require an uninterrupted positioning service. However, the level of resilience required for these applications is difficult to achieve using the popular navigation and positioning systems available at the time of this writing. Most of these systems are dependent on existing infrastructure to function or have certain vulnerabilities that can be too easily exploited by hostile forces. Mobile ad-hoc networks can bypass some of these prevalent issues making them an auspicious topic for positioning and navigation research and development. Such networks consist of portable devices that collaborate to form wireless communication links with one another and collectively carry out vital network functions independent of any fixed centralized infrastructure. The purpose of the research presented in this thesis is to adapt the protocols of an existing narrowband mobile ad-hoc communications system provided by Terrafix to enable range measuring for positioning. This is done by extracting transmission and reception timestamps of signals exchanged between neighbouring radios in the network with the highest precision possible. However, many aspects of the radios forming this network are generally not conducive to precise ranging, so the ranging protocols implemented need to either maneuver around these shortcomings or compensate for loss of precision caused. In particular, the narrow bandwidth of the signals that drastically reduces the resolution of symbol timing. The objective is to determine what level of accuracy and precision is possible using this radio network and whether one can justify investment for further development. Early experiments have provided a simple ranging demonstration in a benign environment, using the existing synchronization protocols, by extracting time data. The experiments have then advanced to the radio’s signal processing to adjust the synchronization protocols for maximize symbol timing precision and correct for clock drift. By implementing innovative synchronization techniques to the radio network, ranging data collected under benign conditions can exhibit a standard deviation of less than 3m. The lowest standard deviation achieved using only the existing methods of synchronization was over two orders of magnitude greater. All this is achieved in spite of the very narrow 10−20kHz bandwidth of the radio signals, which makes producing range estimates with an error less than 10−100m much more challenging compared to wider bandwidth systems. However, this figure is beholden to the relative motion of neighbouring radios in the network and how frequently range estimates need to be made. This thesis demonstrates how such a precision may be obtained and how this figure is likely to hold up when applied in conditions that are not ideal

CAROLS: A New Airborne L-Band Radiometer for Ocean Surface and Land Observations

The “Cooperative Airborne Radiometer for Ocean and Land Studies” (CAROLS) L-Band radiometer was designed and built as a copy of the EMIRAD II radiometer constructed by the Technical University of Denmark team. It is a fully polarimetric and direct sampling correlation radiometer. It is installed on board a dedicated French ATR42 research aircraft, in conjunction with other airborne instruments (C-Band scatterometer—STORM, the GOLD-RTR GPS system, the infrared CIMEL radiometer and a visible wavelength camera). Following initial laboratory qualifications, three airborne campaigns involving 21 flights were carried out over South West France, the Valencia site and the Bay of Biscay (Atlantic Ocean) in 2007, 2008 and 2009, in coordination with in situ field campaigns. In order to validate the CAROLS data, various aircraft flight patterns and maneuvers were implemented, including straight horizontal flights, circular flights, wing and nose wags over the ocean. Analysis of the first two campaigns in 2007 and 2008 leads us to improve the CAROLS radiometer regarding isolation between channels and filter bandwidth. After implementation of these improvements, results show that the instrument is conforming to specification and is a useful tool for Soil Moisture and Ocean Salinity (SMOS) satellite validation as well as for specific studies on surface soil moisture or ocean salinity

Development of Radio Frequency Interference Detection Algorithm for Passive Microwave Remote Sensing

Radio Frequency Interference (RFI) signals are man-made sources that are increasingly plaguing passive microwave remote sensing measurements. RFI is of insidious nature, with some signals low power enough to go undetected but large enough to impact science measurements and their results. With the launch of the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite in November 2009 and the upcoming launches of the new NASA sea-surface salinity measuring Aquarius mission in June 2011 and soil-moisture measuring Soil Moisture Active Passive (SMAP) mission around 2015, active steps are being taken to detect and mitigate RFI at L-band. An RFI detection algorithm was designed for the Aquarius mission. The algorithm performance was analyzed using kurtosis based RFI ground-truth. The algorithm has been developed with several adjustable location dependant parameters to control the detection statistics (false-alarm rate and probability of detection). The kurtosis statistical detection algorithm has been compared with the Aquarius pulse detection method. The comparative study determines the feasibility of the kurtosis detector for the SMAP radiometer, as a primary RFI detection algorithm in terms of detectability and data bandwidth. The kurtosis algorithm has superior detection capabilities for low duty-cycle radar like pulses, which are more prevalent according to analysis of field campaign data. Most RFI algorithms developed have generally been optimized for performance with individual pulsed-sinusoidal RFI sources. A new RFI detection model is developed that takes into account multiple RFI sources within an antenna footprint. The performance of the kurtosis detection algorithm under such central-limit conditions is evaluated. The SMOS mission has a unique hardware system, and conventional RFI detection techniques cannot be applied. Instead, an RFI detection algorithm for SMOS is developed and applied in the angular domain. This algorithm compares brightness temperature values at various incidence angles for a particular grid location. This algorithm is compared and contrasted with other algorithms present in the visibility domain of SMOS, as well as the spatial domain. Initial results indicate that the SMOS RFI detection algorithm in the angular domain has a higher sensitivity and lower false-alarm rate than algorithms developed in the other two domains.Ph.D.Atmospheric and Space SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/86308/1/samisra_1.pd

Roadmap on signal processing for next generation measurement systems

Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of signals that can be enhanced and analysed for information extraction and quantification. The recent advances in artificial intelligence and machine learning are shifting the research attention towards intelligent, data-driven, signal processing. This roadmap presents a critical overview of the state-of-the-art methods and applications aiming to highlight future challenges and research opportunities towards next generation measurement systems. It covers a broad spectrum of topics ranging from basic to industrial research, organized in concise thematic sections that reflect the trends and the impacts of current and future developments per research field. Furthermore, it offers guidance to researchers and funding agencies in identifying new prospects.AerodynamicsMicrowave Sensing, Signals & System

Advances in Sonar Technology

The demand to explore the largest and also one of the richest parts of our planet, the advances in signal processing promoted by an exponential growth in computation power and a thorough study of sound propagation in the underwater realm, have lead to remarkable advances in sonar technology in the last years.The work on hand is a sum of knowledge of several authors who contributed in various aspects of sonar technology. This book intends to give a broad overview of the advances in sonar technology of the last years that resulted from the research effort of the authors in both sonar systems and their applications. It is intended for scientist and engineers from a variety of backgrounds and even those that never had contact with sonar technology before will find an easy introduction with the topics and principles exposed here

General Interference Suppression Technique For Diversity Wireless Rece

The area of wireless transceiver design is becoming increasingly important due to the rapid growth of wireless communications market as well as diversified design specifications. Research efforts in this area concentrates on schemes that are capable of increasing the system capacity, providing reconfigurability/reprogrammability and reducing the hardware complexity. Emerging topics related to these goals include Software Defined Radio, Multiple-Input-Multiple-Output (MIMO) Systems, Code Division Multiple Access, Ultra-Wideband Systems, etc. This research adopts space diversity and statistical signal processing for digital interference suppression in wireless receivers. The technique simplifies the analog front-end by eliminating the anti-aliasing filters and relaxing the requirements for IF bandpass filters and A/D converters. Like MIMO systems, multiple antenna elements are used for increased frequency reuse. The suppression of both image signal and Co-Channel Interference (CCI) are performed in DSP simultaneously. The signal-processing algorithm used is Independent Component Analysis (ICA). Specifically, the fixed-point Fast-ICA is adopted in the case of static or slow time varying channel conditions. In highly dynamic environment that is typically encountered in cellular mobile communications, a novel ICA algorithm, OBAI-ICA, is developed, which outperforms Fast-ICA for both linear and abrupt time variations. Several practical implementation issues are also considered, such as the effect of finite arithmetic and the possibility of reducing the number of antennas