Spectrum Sensing Algorithms for Cognitive Radio Applications

Future wireless communications systems are expected to be extremely dynamic, smart and capable to interact with the surrounding radio environment. To implement such advanced devices, cognitive radio (CR) is a promising paradigm, focusing on strategies for acquiring information and learning. The first task of a cognitive systems is spectrum sensing, that has been mainly studied in the context of opportunistic spectrum access, in which cognitive nodes must implement signal detection techniques to identify unused bands for transmission. In the present work, we study different spectrum sensing algorithms, focusing on their statistical description and evaluation of the detection performance. Moving from traditional sensing approaches we consider the presence of practical impairments, and analyze algorithm design. Far from the ambition of cover the broad spectrum of spectrum sensing, we aim at providing contributions to the main classes of sensing techniques. In particular, in the context of energy detection we studied the practical design of the test, considering the case in which the noise power is estimated at the receiver. This analysis allows to deepen the phenomenon of the SNR wall, providing the conditions for its existence and showing that presence of the SNR wall is determined by the accuracy of the noise power estimation process. In the context of the eigenvalue based detectors, that can be adopted by multiple sensors systems, we studied the practical situation in presence of unbalances in the noise power at the receivers. Then, we shift the focus from single band detectors to wideband sensing, proposing a new approach based on information theoretic criteria. This technique is blind and, requiring no threshold setting, can be adopted even if the statistical distribution of the observed data in not known exactly. In the last part of the thesis we analyze some simple cooperative localization techniques based on weighted centroid strategies.

Performance analysis of different sensing techniques in Cognitive Radio Networks.

The spectrum of radiofrequency is distributed in such a way that it is fixed to certain users called licensed users and it cannot be used by unlicensed users even though the spectrum is not in use. This inefficient use of spectrum leads to spectral holes. To overcome the problem of spectral holes and increase the efficiency of the spectrum, Cognitive Radio (CR) was used and all simulation work was done on MATLAB. Here analyzed the performance of different spectrum sensing techniques as Match filter based spectrum sensing and energy detection, which depend on various factors, systems such as Numbers of input, signal-to-noise ratio ( SNR Ratio), QPSK system and BPSK system, and different fading channels, to identify the best possible channels and systems for spectrum sensing and improving the probability of detection. The study resulted that an averaging filter being better than an IIR filter. As the number of inputs and SNR increased, the probability of detection also improved. The Rayleigh fading channel has a better performance compared to the Rician and Nakagami fading channel.

Detection of exotic massive hadrons in ultrahigh energy cosmic ray telescopes

We investigate the detection of exotic massive strongly interacting hadrons (uhecrons) in ultrahigh energy cosmic ray telescopes. The conclusion is that experiments such as the Pierre Auger Observatory have the potential to detect these particles. It is shown that uhecron showers have clear distinctive features when compared to proton and nuclear showers. The simulation of uhecron air showers, and its detection and reconstruction by fluorescence telescopes, is described. We determine basic cuts in observables that will separate uhecrons from the cosmic ray bulk, assuming this is composed by protons. If these are composed by a heavier nucleus, the separation will be much improved. We also discuss photon induced showers. The complementarity between uhecron detection in accelerator experiments is discussed.

Lanthanide Chelates as Donors in Fluorescence Resonance Energy Transfer: Exciting Prospects for Bioaffinity Assay Detection

Fluorescence resonance energy transfer (FRET) is a non-radiative energy transfer from a fluorescent donor molecule to an appropriate acceptor molecule and a commonly used technique to develop homogeneous assays. If the emission spectrum of the donor overlaps with the excitation spectrum of the acceptor, FRET might occur. As a consequence, the emission of the donor is decreased and the emission of the acceptor (if fluorescent) increased. Furthermore, the distance between the donor and the acceptor needs to be short enough, commonly 10-100 Å. Typically, the close proximity between the donor and the acceptor is achieved via bioaffinity interactions e.g. antibody binding antigen. Large variety of donors and acceptors exist. The selection of the donor/acceptor pair should be done not only based on the requirements of FRET but also the performance expectancies and the objectives of the application should be considered. In this study, the exceptional fluorescence properties of the lanthanide chelates were employed to develop two novel homogeneous immunoassays: a non-competitive hapten (estradiol) assay based on a single binder and a dual-parametric total and free PSA assay. In addition, the quenching efficiencies and energy transfer properties of various donor/acceptor pairs were studied. The applied donors were either europium(III) or terbium(III) chelates; whereas several organic dyes (both fluorescent and quenchers) acted as acceptors. First, it was shown that if the interaction between the donor/acceptor complexes is of high quality (e.g. biotin-streptavidin) the fluorescence of the europium(III) chelate could be quenched rather efficiently. Furthermore, the quenching based homogeneous non-competitive assay for estradiol had significantly better sensitivity (~67 times) than a corresponding homogeneous competitive assay using the same assay components. Second, if the acceptors were chosen to emit at the emission minima of the terbium(III) chelate, several acceptor emissions could be measured simultaneously without significant cross-talk from other acceptors. Based on these results, the appropriate acceptors were chosen for the dual-parameter assay. The developed homogeneous dual-parameter assay was able to measure both total and free PSA simultaneously using a simple mix and measure protocol. Correlation of this assay to a heterogeneous single parameter assay was excellent (above 0.99 for both) when spiked human plasma samples were used. However, due to the interference of the sample material, the obtained concentrations were slightly lower with the homogeneous than the heterogeneous assay, especially for the free PSA. To conclude, in this work two novel immunoassay principles were developed, which both are adaptable to other analytes. However, the hapten assay requires a rather good antibody with low dissociation rate and high affinity; whereas the dual-parameter assay principle is applicable whenever two immunometric complexes can form simultaneously, provided that the requirements of FRET are fulfilled.

Early detection of metabolic and energy disorders by thermal time series stochastic complexity analysis

Maintenance of thermal homeostasis in rats fed a high-fat diet (HFD) is associated with changes in their thermal balance. The thermodynamic relationship between heat dissipation and energy storage is altered by the ingestion of high-energy diet content. Observation of thermal registers of core temperature behavior, in humans and rodents, permits identification of some characteristics of time series, such as autoreference and stationarity that fit adequately to a stochastic analysis. To identify this change, we used, for the first time, a stochastic autoregressive model, the concepts of which match those associated with physiological systems involved and applied in male HFD rats compared with their appropriate standard food intake age-matched male controls (n=7 per group). By analyzing a recorded temperature time series, we were able to identify when thermal homeostasis would be affected by a new diet. The autoregressive time series model (AR model) was used to predict the occurrence of thermal homeostasis, and this model proved to be very effective in distinguishing such a physiological disorder. Thus, we infer from the results of our study that maximum entropy distribution as a means for stochastic characterization of temperature time series registers may be established as an important and early tool to aid in the diagnosis and prevention of metabolic diseases due to their ability to detect small variations in thermal profile.

Constrained surplus energy adaptive blind CDMA detection

The blind minimum output energy (MOE) adaptive detector for code division multiple access (CDMA) signals requires exact knowledge of the received spreading code of the desired user. This requirement can be relaxed by constraining the so-called surplus energy of the adaptive tap-weight vector, but the ideal constraint value is not easily obtained in practice. An algorithm is proposed to adaptively track this value and hence to approach the best possible performance for this class of CDMA detector.

Bone images from dual-energy subtraction chest radiography in the detection of rib fractures

To assess the sensitivity and image quality of chest radiography (CXR) with or without dual-energy subtracted (ES) bone images in the detection of rib fractures.

Improved detection of pulmonary nodules on energy-subtracted chest radiographs with a commercial computer-aided diagnosis software: comparison with human observers

To retrospectively analyze the performance of a commercial computer-aided diagnosis (CAD) software in the detection of pulmonary nodules in original and energy-subtracted (ES) chest radiographs.

Comparison of dual-energy subtraction and electronic bone suppression combined with computer-aided detection on chest radiographs: effect on human observers' performance in nodule detection

The objective of our study was to compare the effect of dual-energy subtraction and bone suppression software alone and in combination with computer-aided detection (CAD) on the performance of human observers in lung nodule detection.

Single-exposure dual-energy subtraction chest radiography: detection of pulmonary nodules and masses in clinical practice

The purpose of this retrospective study was to evaluate the impact of energy subtraction (ES) chest radiography on the detection of pulmonary nodules and masses in daily routine. Seventy-seven patients and 25 healthy subjects were examined with a single exposure digital radiography system. Five blinded readers evaluated first the non-subtracted PA and lateral chest radiographs alone and then together with the subtracted PA soft tissue images. The size, location and number of lung nodules or masses were registered with the confidence level. CT was used as standard of reference. For the 200 total lesions, a sensitivity of 33.5-52.5% was found at non-subtracted and a sensitivity of 43.5-58.5% at energy-subtracted radiography, corresponding to a significant improvement in four of five readers (p < 0.05). However, in three of five readers the rate of false positives was higher with ES. With ES, sensitivity, but not the area under the alternative free-response receiver operating characteristics (AFROC) curve, showed a good correlation with reader experience (R = 0.90, p = 0.026). In four of five readers, the diagnostic confidence improved with ES (p = 0.0036). We conclude that single-exposure digital ES chest radiography improves detection of most pulmonary nodules and masses, but identification of nodules <1 cm and false-positive findings remain a problem.

Endoleak detection with CT angiography in an abdominal aortic aneurysm phantom: effect of tube energy, simulated patient size, and physical properties of endoleaks

To analyze the detection of endoleaks with low-tube-voltage computed tomographic (CT) angiography.

Lung Nodule Detection by Microdose CT Versus Chest Radiography (Standard and Dual-Energy Subtracted).

OBJECTIVE The purpose of this study was to investigate the feasibility of microdose CT using a comparable dose as for conventional chest radiographs in two planes including dual-energy subtraction for lung nodule assessment. MATERIALS AND METHODS We investigated 65 chest phantoms with 141 lung nodules, using an anthropomorphic chest phantom with artificial lung nodules. Microdose CT parameters were 80 kV and 6 mAs, with pitch of 2.2. Iterative reconstruction algorithms and an integrated circuit detector system (Stellar, Siemens Healthcare) were applied for maximum dose reduction. Maximum intensity projections (MIPs) were reconstructed. Chest radiographs were acquired in two projections with bone suppression. Four blinded radiologists interpreted the images in random order. RESULTS A soft-tissue CT kernel (I30f) delivered better sensitivities in a pilot study than a hard kernel (I70f), with respective mean (SD) sensitivities of 91.1% ± 2.2% versus 85.6% ± 5.6% (p = 0.041). Nodule size was measured accurately for all kernels. Mean clustered nodule sensitivity with chest radiography was 45.7% ± 8.1% (with bone suppression, 46.1% ± 8%; p = 0.94); for microdose CT, nodule sensitivity was 83.6% ± 9% without MIP (with additional MIP, 92.5% ± 6%; p < 10(-3)). Individual sensitivities of microdose CT for readers 1, 2, 3, and 4 were 84.3%, 90.7%, 68.6%, and 45.0%, respectively. Sensitivities with chest radiography for readers 1, 2, 3, and 4 were 42.9%, 58.6%, 36.4%, and 90.7%, respectively. In the per-phantom analysis, respective sensitivities of microdose CT versus chest radiography were 96.2% and 75% (p < 10(-6)). The effective dose for chest radiography including dual-energy subtraction was 0.242 mSv; for microdose CT, the applied dose was 0.1323 mSv. CONCLUSION Microdose CT is better than the combination of chest radiography and dual-energy subtraction for the detection of solid nodules between 5 and 12 mm at a lower dose level of 0.13 mSv. Soft-tissue kernels allow better sensitivities. These preliminary results indicate that microdose CT has the potential to replace conventional chest radiography for lung nodule detection.