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Spectrum sensing is one of the most crucial tasks a cognitive radio has to carry out in order to decide whether a licensed spectrum can be used without causing interference to the licensed or the Primary Users (PU). Many techniques exist in the literature for satisfactory detection performance. However, in many cases, an additive white Gaussian noise is assumed, which is an oversimplified assumption...
Algorithms for Robust Fault Detection and Identification (RFDI) in dynamic systems strive to be sensitive to faults in plant components, while being insensitive to plant and noise model uncertainties. In the field of signal detection with applications such as radar and medical images, sensitivity to signals of interest is also an objective, while robustness is concerned with undesirable interferences...
Various methods for detecting the fiducial points of the pulse wave signals are discussed. A new simple detector of the fiducial points based on the application of the first derivative operator, set of nonlinear transformations and adaptive threshold is described. The efficiency of various detectors of the beat points of pulse wave signal in the presence of interferences of various origins and intensities...
This paper proposes a generalized joint probabilistic (JPDA) filter for tracking multiple maneuvering targets in situations of observations with unknown random characteristics. In the proposed filter, the joint association probabilities in the standard JPDA filter are reconstructed by utilizing the generalized association probabilities of observations belonging to the targets. To calculate the generalized...
For its simplicity and ease of implementation, Energy detection (ED) is attractive for spectrum sensing in cognitive radio (CR) systems. In ED, the energy captured is compared against a fixed detection threshold, which is estimated as a function of the noise power. Uncertainties caused by the imperfect knowledge of the noise power, referred to as noise uncertainty, leads to a reduced performance of...
In this paper, spectrum sensing in cognitive radio systems is studied for non-Gaussian channels in the presence of prior distribution uncertainty. In most practical cases, some amount of prior information about signals of primary users is available to secondary users but that information is never perfect. In order to design optimal spectrum sensing algorithms in such cases, we propose to employ the...
We present a novel learning method using activity grammars capable of learning reusable task components from a reasonably small number of samples under noisy conditions. Our linguistic approach aims to extract the hierarchical structure of activities which can be recursively applied to help recognize unforeseen, more complicated tasks that share the same underlying structures. To achieve this goal,...
We illuminate a photon-number-resolving transition edge sensor with strong pulses of light containing up to 6.7 million photons (0.85 pJ per pulse). These bright pulses heat the sensor far beyond its transition edge into the normal resistance regime. We show that the sensor operates from the single-photon-counting regime to picowatt levels of light and that the detection noise is below shot-noise...
We consider the problem of detecting a primary user in a cognitive radio network by employing multiple antennas at the cognitive receiver. In vehicular applications, cognitive radios typically transit regions with differing densities of primary users. Therefore, speed of detection is key, so detection based on a small number of samples is particularly advantageous for vehicular applications. Without...
We are developing a single-electron turnstile based on a nanoscale superconductor-insulator-normal-metal-insulator-superconductor (SINIS) structure. The goal is to obtain the frequency to current conversion I = ef with a relative uncertainty < 10−8 which would be sufficient for a quantum-based standard of electric current. Finally, the quantum current standard will be compared against the quantum...
Scaled largest eigenvalue based detection is an ideal solution to spectrum sensing problem in cognitive radio networks. However, results on the sensing performance are very limited. In this paper, we analytically investigate the detection performance by deriving simple and accurate test statistics distributions. These results are obtained by taking advantage of properties of the Mellin transform for...
This paper considers the problem of weak signal detection in the presence of navigation data bits for Global Navigation Satellite System (GNSS) receivers. Typically, a set of partial coherent integration outputs are non-coherently accumulated to combat the effects of model uncertainties such as the presence of navigation data-bits and/or frequency uncertainty, resulting in a sub-optimal test statistic...
Spectrum sensing is a key component in cognitive radio networks. The existing results so far primarily focus on single primary user detection. Little is known in the most practical and critical setting when multiple primary users exist. In this paper, we aim to address this problem by studying an optimal detector in the presence of multiple primary users. Specifically, a simple and accurate analytical...
One of the main challenges in cognitive radio (CR) communications lies in the system robustness to uncertainties. In this paper, we examine the impact of the noise power uncertainty on the performance of various detectors in CR networks. We consider both single and multiple CR nodes. For the single CR case, we compare the performance of the energy and likelihood ratio test (LRT) detectors in the presence...
Spectrum sensing is one of the most important technologies in the implementation of cognitive radio system using dynamic spectrum resource management. Since the performance of the widely used energy detector based approach will experience a significant loss under a small noise fluctuation, especially in low SNR, we proposed a two-step spectrum sensing in this paper. With dual-threshold energy detection...
As a method of image feature extraction, corner detection algorithm has been applied in many fields. Uncertainty evaluation of corner detection is an important approach to evaluating the reliability of corner detection. This paper presents a new method for uncertainty evaluation of corner detection. A mathematical model which relates the uncertainty of pixel intensity with the pixel intensity and...
This paper considers the problem of spectrum sensing in cognitive radio networks when the primary user employs Orthogonal Frequency Division Multiplexing (OFDM). We specifically consider the scenario when the channel between the primary and a secondary user is frequency selective. We develop cooperative sequential detection algorithms based on energy detectors. We modify the detectors to mitigate...
Cognitive radio is based on dynamic spectrum sharing in order to increase spectrum efficiency. In this approach, which is opposite of the current spectrum allocation, a secondary user (unlicensed) shares a frequency band with designated primary users (licensed) without causing interference or performance degradation to the primary users. Cognitive radio needs reliable spectrum sensing techniques to...
At the National Research Council in Ottawa, the conventional Hysteretic Josephson Array Voltage System (HJVS) and the Programmable Josephson Array Voltage System (PJVS) associated with the watt balance experiment have been directly compared. This direct comparison of Josephson array systems uses an improved automated biasing technique for the hysteretic array. The comparison is being performed with...
In this paper, we consider the sensing of primary user signal by exploiting the receive antenna correlation properties in cognitive radio systems. Since the signal and noise have different statistical correlation characteristics, it can be possible to design a detection scheme that does not need the apriori information on the noise, making it robust to noise uncertainty. Simulation results show that...
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