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In this paper, a novel detection criterion is proposed to decide whether primary user (PU) exists based on joint analysis of the variance and correlation for observation signal, considering a correlation within the observed signal. Simultaneously, the corresponding detection thresholds are also designed. Simulation experiments verify the proposed method suits for the observation signal in Additive...
Cooperative spectrum sensing scheme has a good effect on the problem of hidden terminal, multipath effect and deep fading. There is also a technique which can make a full use of spectrum resources. In our proposed scheme, clustering is a good idea to avoid the burden of large amount of processing data in fusion center, to reduce the magnitude of cognitive information transmission in the network. The...
In order to obtain better performance at low SNR regimes and reduce computational complexity in wideband sensing, a novel cyclostationary spectrum sensing (CSS) algorithm exploiting partial QR decomposition is proposed in this paper. At the first step of the CSS algorithm, spectral correlation functions (SCFs) for sampled signals that exhibit cyclostationary are calculated by secondary user (SU) to...
In cognitive radio networks (CRN), underlay spectrum sharing allows secondary users (SUs) to utilize the spectrum on which the primary users (PUs) are working at the same time, without introducing intolerant interference. Interference alignment (IA) is a prospective technique for interference management, and can significantly improve the performance of cognitive radio (CR) networks. Besides, power...
This paper introduces an improved cooperative spectrum sensing (CSS) algorithm for cognitive radio (CR) networks based on the machine learning technique. In this scheme, spectrum sensing consists of two steps. The offline training is performed by K-means clustering method and the threshold is defined by the classification result towards unsupervised data. As for the online classification stage, the...
Spectrum sensing is a key component in cognitive radio networks, which allows secondary users to communicate without causing harmful interference to primary users. Cyclostationary feature based spectrum sensing has proven preferable to other methods under low signal-to-noise ratio conditions. To detect the presence of primary signals, conventional cyclostationary feature based schemes tend to simply...
As an effective approach to improve spectrum efficiency, cognitive radio network make it possible for secondary users (SU) to share the spectrum with primary users (PU), on the condition that the primary users have preemptive priority. In this paper, we applied the Dynamic Chinese restaurant game, which ideally modeled the spectrum sensing and access in cognitive network. We propose the use of Multilayer...
Deep Belief Networks (DBN) is a very powerful algorithm in deep learning. The DBN has been effectively applied in many areas of machine learning, such as computer vision (CV) and natural language processing (NLP). With the help of deep architecture, their accuracy has been largely improved and their human annotation data which traditional machine learning algorithm extremely rely on could be reduced...
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