scholarly journals Conventional Combining Scheme in Cooperative Spectrum Sensing

2020 ◽  
Vol 9 (7) ◽  
pp. 299-303
Keyword(s):  
Spectrum Sensing ◽  
Software Defined Radio ◽  
Cooperative Spectrum Sensing ◽  
Primary User ◽  
Detection Error ◽  
White Hole ◽  
Spectrum Hole ◽  
Soft Combining ◽  
Fusion Centre ◽  
Individual Node

Spectrum Sensing (SS) is a key constituent of software defined radio (SDR) or Cognitive radio (CR). Spectrum sensing (SS) investigate the white hole in allotted spectrum to the primary user. Cooperative spectrum sensing (CSS) has work in a best manner than any other spectrum sensing (SS) technique to detect white space or spectrum hole in the licensed spectrum. In this paper we compare various combining scheme that are to be perform at the Fusion centre (FC). Fusion centre (FC) is the central part of Cooperative spectrum sensing (CSS) that combines individual node decision. Simulation has performed for hard and soft combining scheme. According to the simulation the soft combining scheme performed better then hard combining scheme but the complexity and bandwidth (BW) requirement in the soft combining is more than hard combining scheme. In the proposed paper we also explore detection error that is to be present in various combining scheme.

Cooperative Spectrum Sensing Under Double Threshold With Censoring and Hybrid Spectrum Access Schemes in Cognitive Radio Network

2019 ◽  
pp. 164-188
Author(s):  
Abhijit Bhowmick ◽  
Sanjay Dhar Roy ◽  
Sumit Kundu
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Energy Detection ◽  
Primary User ◽  
Spectrum Access ◽  
Access Scheme ◽  
Transmission Overhead ◽  
Fusion Centre ◽  
Double Threshold

The spectrum sensing performance in cooperative cognitive radio (CR) network is studied under a double threshold (DTH)-based detection with censoring of CRs, and thereafter, the study is extended for a hybrid spectrum access scheme in presence of Rayleigh faded sensing (S) and reporting (R) channels. In spectrum sensing, a CR employs an energy detection to detect the presence of primary user (PU) and compares the received energy statistics with the DTH. The CRs with energy statistics lying in fuzzy zone are not allowed to send their sensing information to the fusion centre (FC). Further, the qualified CRs are censored (rank-based and threshold-based censoring) to report their decisions based on quality of R-channel. The incorporation of DTH-based sensing and censoring of CRs not only improves the detection performance but also reduces the transmission overhead. In spectrum access, two hybrid spectrum access schemes, namely conventional hybrid spectrum access scheme (CHSAS) and a modified hybrid spectrum access scheme (MHSAS) are studied and compared.

scholarly journals Cooperative Spectrum Sensing Based on Multi-Features Combination Network in Cognitive Radio Network

Entropy ◽  
2022 ◽  
Vol 24 (1) ◽  
pp. 129
Author(s):  
Mingdong Xu ◽  
Zhendong Yin ◽  
Yanlong Zhao ◽  
Zhilu Wu
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Cooperative Spectrum Sensing ◽  
Signal To Noise Ratio ◽  
Primary User ◽  
Radio Spectrum ◽  
Local Information ◽  
Channel State ◽  
Single Node

cognitive radio, as a key technology to improve the utilization of radio spectrum, acquired much attention. Moreover, spectrum sensing has an irreplaceable position in the field of cognitive radio and was widely studied. The convolutional neural networks (CNNs) and the gate recurrent unit (GRU) are complementary in their modelling capabilities. In this paper, we introduce a CNN-GRU network to obtain the local information for single-node spectrum sensing, in which CNN is used to extract spatial feature and GRU is used to extract the temporal feature. Then, the combination network receives the features extracted by the CNN-GRU network to achieve multifeatures combination and obtains the final cooperation result. The cooperative spectrum sensing scheme based on Multifeatures Combination Network enhances the sensing reliability by fusing the local information from different sensing nodes. To accommodate the detection of multiple types of signals, we generated 8 kinds of modulation types to train the model. Theoretical analysis and simulation results show that the cooperative spectrum sensing algorithm proposed in this paper improved detection performance with no prior knowledge about the information of primary user or channel state. Our proposed method achieved competitive performance under the condition of large dynamic signal-to-noise ratio.

Deep Cooperative Spectrum Sensing Utilizing Recurrent Convolutional Neural Networks

2020 ◽  
Author(s):  
Rahil Sarikhani ◽  
Farshid Keynia
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Deep Learning ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Recurrent Neural Network ◽  
Cooperative Spectrum Sensing ◽  
Primary User ◽  
Secondary Users ◽  
Spectrum Holes

Abstract Cognitive Radio (CR) network was introduced as a promising approach in utilizing spectrum holes. Spectrum sensing is the first stage of this utilization which could be improved using cooperation, namely Cooperative Spectrum Sensing (CSS), where some Secondary Users (SUs) collaborate to detect the existence of the Primary User (PU). In this paper, to improve the accuracy of detection Deep Learning (DL) is used. In order to make it more practical, Recurrent Neural Network (RNN) is used since there are some memory in the channel and the state of the PUs in the network. Hence, the proposed RNN is compared with the Convolutional Neural Network (CNN), and it represents useful advantages to the contrast one, which is demonstrated by simulation.

Energy-Efficient Cooperative Spectrum Sensing for Cognitive Radio Networks

2015 ◽  
pp. 100-121
Author(s):  
Saud Althunibat ◽  
Sandeep Narayanan ◽  
Marco Di Renzo ◽  
Fabrizio Granelli
Keyword(s):  
Energy Consumption ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
High Energy ◽  
Radio Networks ◽  
Participation Decision ◽  
Consumption Energy ◽  
Fusion Centre

One of the main problems of Cooperative Spectrum Sensing (CSS) in cognitive radio networks is the high energy consumption. Energy is consumed while sensing the spectrum and reporting the results to the fusion centre. In this chapter, a novel partial CSS is proposed. The main concern is to reduce the energy consumption by limiting the number of participating users in CSS. Particularly, each user individually makes the participation decision. The energy consumption in a CSS round is expected by the user itself and compared to a predefined threshold. The corresponding user will participate only if the expected amount of energy consumed is less than the participation threshold. The chapter includes optimizing the participation threshold for energy efficiency maximization. The simulation results show a significant reduction in the energy consumed compared to the conventional CSS approach.

scholarly journals SDR Based Energy Detection Spectrum Sensing in Cognitive Radio for Real Time Video Transmission

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Rupali B. Patil ◽  
K. D. Kulat ◽  
A. S. Gandhi
Keyword(s):  
Cognitive Radio ◽  
Real Time ◽  
Spectrum Sensing ◽  
Software Defined Radio ◽  
Video Transmission ◽  
Energy Detection ◽  
Primary User ◽  
Data Traffic ◽  
Real Time Transmission ◽  
Is Design

Cognitive radio is a budding approach which helps to address the imminent spectrum crisis by dynamic spectrum allocation and support the increased data traffic with an intelligent mechanism of Software Defined Radio (SDR). SDR avoid the frequent modifications in the hardware structure with the use of software defined protocols. The main novelty of the paper is an effective implementation of CR using energy based spectrum sensing method which is done on GNU radio for real time transmission of video as a primary user. From evaluation results, one can see that the proposed system can indicate the frequency band occupancy by setting the detection output. Detection output changes to one with start of video transmission. Motivation behind this work is design of a spectrum sensing method which is best suited for detection of white spaces during the transmission of video as a primary user on SDR platform.

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