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The quasi-likelihood algorithm detection of rectangle ultra-wideband quasi-radiosignal with unknown amplitude, initial phase and duration has been synthesized. The statistical characteristics of the efficiency synthesized detection algorithm — false alarm probability and probability of missing a signal, have been found.
A new detection algorithm for direct sequence spread spectrum (DSSS) signals using peak-to-average power ratio (PAPR) is proposed. The received signals are divided into several blocks. Then we calculate peak-to-average power ratio of each block and we use the average of peak-to-average power ratios as test statistics. The advantage of the proposed algorithm is no need to estimate noise variance. Additionally,...
Ambient backscatter is a new technology that utilizes environmental wireless signals to enable battery-free devices to communicate with each other. In this paper, we investigate the problem of signal detection for the full duplex wireless system utilizing ambient backscatter. Since one of the key technologies of full duplex wireless system is self-interference cancellation, we first estimate the channel...
In this paper, as binary modulation schemes, the differential on-off keying (DOOK) system, which can achieve anti-background noise capability and high data transmission efficiency, is considered. In order to solve the synchronization slip, a visible-light framed DOOK system embedding {-1,+1}-synchronization signal pattern is proposed. Moreover, theoretical formulas of detection and false alarm probability...
This paper presents the design technique of the selection diversity combining based spectrum sensing in cognitive radio networks. In general, the selection diversity combining scheme requires period to choose an optimal element, and spectrum sensing also requires period to detect a target signal. Because spending a long time for the selection and sensing increases the accuracy of the selection and...
The quasi-likelihood algorithm detection of rectangle ultra-wideband quasi-radiosignal with unknown amplitude, initial phase and duration has been synthesized. The statistical characteristics of the efficiency synthesized detection algorithm — false alarm probability and probability of missing a signal, have been found.
This paper presents a computationally efficient cyclostationarity detection based spectrum sensing in cognitive radio. Traditionally, several cyclostationarity detection based spectrum sensing techniques with a low computational complexity have been presented, e.g., peak detector (PD) or maximum cyclic autocorrelation selection (MCAS), and so on. Compared to both techniques, PD can be affected the...
In this paper, we address the problem of signal detection in multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system by using auto-encoder (AE) network and extreme learning machine (ELM). The existing signal detection algorithms, such as zero-forcing successive-interference-cancellation (ZF-SIC), minimum-mean-square-error successive-interference-cancellation...
Optimal algorithms of band-limited noise signal detection are synthesized. The decision on the presence or absence of a signal is taken from the result of likelihood functions comparison. The block diagrams of optimal and quasi-optimal detectors are developed. The analytical expressions of probabilistic and power characteristics for different ratios of useful and noise signals are obtained. Curves...
In this work, the inter-dependency of TCM signals is studied. Using this inter-dependency, correlation-based detectors are proposed for spectrum sensing of TCM signals in white Gaussian noise. In particular, a constant false alarm rate (CFAR) detector is presented and its performance is evaluated using simulations. We also describe an application of our detector for the classification of uncoded modulation...
In modern heterogeneous sensor networks huge volumes of information rapidly flow across the system, and it is often too difficult or costly to associate data to the sensors that produced them. Then, the set of observations appears to be unlabeled: What comes from whom? We study the classical problem of detecting a known signal embedded in Gaussian noise, but under the peculiar assumption that the...
Detection of particles from a far-field source is important in many applications, including optical communications, nuclear hazard detection, radioactivity and detection of cosmic particles. In this paper, we revisit the problem of detection of far-field particle sources using a cubical array. For the case when the source location is deterministic, assuming Poisson arrival of particles, we propose...
The problem of detecting an unknown signal embedded in white Gaussian noise is addressed. The detector based on Wilcoxon signed-rank test is proposed as the solution for this problem. The detector analyses the spectrum of a received signal. Detection capability of this detector has been evaluated via mathematical modeling. Comparison with other prevalent detectors has been done.
The resource of radio frequency spectrum is not efficiently managed, and the increased dependence on wireless devices in the modern era just adds to the problem. The concept of cognitive radio aims to overcome the problem of limited radio frequency spectrum by helping to achieve improved spectral management, utilization, and efficiency. One of the ways to improve the efficiency and utilization of...
While most of research in Compressive Sensing (CS) has been focused on reconstruction of the sparse signal from very fewer samples than the ones required by the Shannon-Nyquist sampling theorem, recently there has been a growing interest in performing signal processing directly in the measurement domain. This new area of research is known in the literature as Compressive Signal Processing (CSP). In...
Non-Gaussian noises usually fail many conventional and effective signal detection techniques including the energy detector and the eigenvalue-based detector. The fractional lower order moment (FLOM) based detector has proved to be useful for unknown stochastic signal detection in α-stable distributed noises. However, the fixed exponent prevents the improvement of its performance. This paper presents...
Aiming at pulse detection in practical complex environment applications, a new method based on frequency-domain constant false alarm rate (CFAR) detector is proposed in this paper. First, short time Fourier transform (STFT) is carried out. Then frequency-domain CFAR detector is used to judge whether signal exists or not in each STFT window. Finally the complete pulse is detected by sliding the STFT...
Electrical field sensors are widely used for detecting transient signal in the EMC tests. The traditional method to detect the electrical field sensor signal is single-path detection using spectrum analyzer, which is applicable when the frequency is known. But if the signal is transient during the EMC tests, it often needs to sweep multiple times to detect different frequency points, or test multiple...
Spectrum sensing is the ability to apprise and be aware of the parameters correlated to the radio channel. This paper, proposes a novel feature detection method based on curvelet transform for spectrum sensing. Initially, the received signal is processed by Curvelet transform and then the test statistics are obtained by examining the feature of the signal in the new domain that is compared with the...
Matched Subspace Detector (MSD) is a robust detection scheme used for detection of the target primary user signal buried in high-dimensional noise where the target signal is assumed to be placed in low-rank subspace. In this paper we attempt to present the benefits of MSD detector by providing the performance comparison with some other existing blind signal detection techniques and further confirmed...
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