scholarly journals Wideband Spectrum Sensing Based on Reconfigurable Filter Bank in Cognitive Radio

2019 ◽  
Vol 11 (11) ◽  
pp. 244
Author(s):  
Wang ◽  
Wu ◽  
Yao ◽  
Qin
Keyword(s):  
Fourier Transform ◽  
Spectrum Sensing ◽  
Filter Bank ◽  
Energy Detection ◽  
High Rate ◽  
Idle State ◽  
Trade Off ◽  
Wideband Spectrum Sensing ◽  
Wideband Signals ◽  
Sensing Time

In order to ease the conflict between the bandwidth demand of high-rate wireless communication and the shortage of spectrum resources, a wideband spectrum sensing method based on reconfigurable filter bank (RFB) with adjustable resolution is presented. The wideband signals are uniformly divided into multi-narrowband signals by RFB, which is designed by polyphase uniform Discrete Fourier Transform (DFT) modulation, and each sub-band is sensed by energy detection. According to the idle proportion of detected sub-bands, the number of RFB sub-bands is reset in next spectrum-sensing time. By simulating with collected wideband dataset, the influence of filter bank sub-bands number and idle state proportion on the sensing results is analyzed, and then on the basis of the trade-off between spectrum-sensing resolution and computational complexity, the optimal sub-bands number of filter bank is selected, so as to improve the detection performance and save resources.

Phase Type Viewpoint Spectrum Sensing for Cognitive Radios

Frequenz ◽  
2015 ◽  
Vol 69 (9-10) ◽  
Author(s):  
Mohammadreza Amini ◽  
Asra Mirzavandi
Keyword(s):  
Spectrum Sensing ◽  
Cognitive Radios ◽  
Type Model ◽  
Computationally Efficient ◽  
Channel State ◽  
Secondary Users ◽  
Trade Off ◽  
Phase Type ◽  
Error Probabilities ◽  
Sensing Time

AbstractSpectrum sensing is one of the main functionalities of cognitive radios to find transmission opportunities without interfering primary users’ transmission. The more accurate and efficient the spectrum sensing is, the higher the throughput of secondary and primary networks is achieved. This paper presents adaptive spectrum sensing method based on phase type modelling that is computationally efficient for secondary users to conclude about the channel state (idle or busy) under collision constraint. The parameters of phase type model can be adjusted based on the desired operating point of the receiver sensor in its ROC curve. The presented approach can run a simple trade off between sensing time and the two error probabilities of the receiver sensor i.e. False alarm and Miss-detection, the trade off that cannot be easily achieved in other sensing method.

scholarly journals Compressed Wideband Spectrum Sensing Based on Discrete Cosine Transform

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Yulin Wang ◽  
Gengxin Zhang
Keyword(s):  
Fourier Transform ◽  
Discrete Cosine Transform ◽  
Spectrum Sensing ◽  
Detection Probability ◽  
Compressive Sampling ◽  
Cosine Transform ◽  
Wideband Spectrum Sensing ◽  
Communication Signal ◽  
Dct Domain ◽  
Sparsity Structure

Discrete cosine transform (DCT) is a special type of transform which is widely used for compression of speech and image. However, its use for spectrum sensing has not yet received widespread attention. This paper aims to alleviate the sampling requirements of wideband spectrum sensing by utilizing the compressive sampling (CS) principle and exploiting the unique sparsity structure in the DCT domain. Compared with discrete Fourier transform (DFT), wideband communication signal has much sparser representation and easier implementation in DCT domain. Simulation result shows that the proposed DCT-CSS scheme outperforms the conventional DFT-CSS scheme in terms of MSE of reconstruction signal, detection probability, and computational complexity.

Improved Two-Stage Spectrum Sensing for Cognitive Radio Networks

2019 ◽  
Vol 23 (6) ◽  
pp. 1052-1062
Author(s):  
Fidel Wasonga ◽  
Thomas O. Olwal ◽  
Adnan Abu-Mahfouz ◽  
◽  
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Feature Detection ◽  
Energy Detection ◽  
Probability Of Detection ◽  
Detection Accuracy ◽  
Two Stage ◽  
Probability Of Error ◽  
Average Spectrum ◽  
Sensing Time

Cognitive radio employs an opportunistic spectrum access approach to ensure efficient utilization of the available spectrum by secondary users (SUs). To allow SUs to access the spectrum opportunistically, the spectrum sensing process must be fast and accurate to avoid possible interference with the primary users. Previously, two-stage spectrum sensing methods were proposed that consider the sensing time and sensing accuracy parameters independently at the cost of a non-optimal spectrum sensing performance. To resolve this non-optimality issue, we consider both parameters in the design of our spectrum sensing scheme. In our scheme, we first derive optimal thresholds using an optimization equation with an objective function of maximizing the probability of detection, subject to the minimal probability of error. We then minimize the average spectrum sensing time using signal-to-noise ratio estimation. Our simulation results show that the proposed improved two-stage spectrum sensing (ITSS) scheme provides a 4%, 7%, and 6% better probability of detection accuracy rate than two-stage combinations of energy detection (ED) and maximum eigenvalue detection, energy detection and cyclostationary feature detection (CFD), and ED and combination of maximum-minimum eigenvalue (CMME) detection, respectively. The ITSS is superior also to single-stage ED by 19% and shows an improved average spectrum sensing time.

A Wideband Spectrum-Sensing Processor With Adaptive Detection Threshold and Sensing Time

2011 ◽  
Vol 58 (11) ◽  
pp. 2765-2775 ◽  
Author(s):  
Tsung-Han Yu ◽  
Oussama Sekkat ◽  
Santiago Rodriguez-Parera ◽  
Dejan Markovic ◽  
Danijela Cabric
Keyword(s):  
Spectrum Sensing ◽  
Detection Threshold ◽  
Adaptive Detection ◽  
Wideband Spectrum Sensing ◽  
Sensing Time
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