The key challenge of spectrum sensing is the Detection of weak signals or primary user in noise with a very small probability of miss detection, which requires better understanding of very low SNR regimes. Cognitive radio allows unlicensed users to access licensed frequency bands through dynamic spectrum access so as to reduce spectrum scarcity. The spectrum sensing problem has gained new aspec...

Current static spectrum assignment policy leads to the shortage of the spectrum for launching newer telecom cooperation or enhancing the existing ones. To address this issue of inefficient spectrum utilization, a new term Dynamic Spectrum Access has emerged. Cognitive Radio is the most decisive technology for the successful deployment of Dynamic Spectrum Access. Spectrum sensing plays a vital r...

Through the analyzing of limitations on wavelet threshold filter de-noising, this paper applies wavelet filter based on compressed sensing to reduce the signal noise of spectral signals, and compares the two methods through experiments. The results of experiments shown that the wavelet filter based on compressed sensing can effectively reduce the signal noise of spectral signal. The de-noising ...

In this paper, we study the impact of secondary user (SU) sensing range on spectrum access opportunity in cognitive radio networks. We first derive a closed-form expression of spectrum access opportunity by taking into account the random variations in number, locations and transmitted powers of primary users (PUs). Then, we show how SU sensing range affects spectrum access opportunity, and the ...

Spectrum sensing is the key element in cognitive radio networks for detecting the primary users. Due to the destructive conditions of sensing channel such as multipath fading and shadowing, local sensing is not fitting the requirements for reliable detection. Therefore, cooperative spectrum sensing is introduced to detect the primary user more accurately. Clustering approach is considered as an...

The rapid growth of wireless applications has increases the importance for efficient utilization of the scarce spectrum resources. Cognitive Radio Network (CRN) is an emerging technology which leads to solve these problems through dynamic utilization of the unused licensed spectrum. Spectrum sensing is a key function of cognitive radio to find the spectrum holes and Collaborative or cooperative...

Spectrum sensing is a key part of cognitive radio networks (CRNs). There have been many works done on improving the accuracy of spectrum sensing results. In this paper, we focus on the phase before spectrum sensing is performed, that is, how to select a channel for sensing. We make use of the fact that nodes located in close geographical locations share similar channel information or sensing re...

Wideband spectrum sensing is one of the most challenging aspects of Cognitive Radio Networks (CRNs). It should be performed as fast and as accurate as possible. Traditional wideband spectrum sensing techniques require excessively high sampling rate analog-to-digital converters (ADCs). Compressed sensing was considered to enable wideband spectrum sensing at a much lower sampling rate below the N...

Spectrum sensing is a key element for cognitive radio and is process of obtaining awareness about the radio spectrum in order to detect the presence of other users. In this paper we study the performance of different spectrum sensing techniques in terms of detection performance and required SNR, based on theoretical expressions. Keywordscognitive radio; spectrum sensing; energy detection;matced...

Spectrum sensing is an essential function that enables cognitive radio technology to explore spectral holes and resourcefully access them without any harmful interference to the licenses user. Spectrum sensing done by a single node is highly affected by fading and shadowing. Thus, to overcome this, cooperative spectrum sensing was introduced. Currently, the advancements in multiple antennas hav...