Correlation Based Secondary Users Selection for Cooperative Spectrum Sensing Network

Security is a pending challenge in cooperative spectrum sensing (CSS) as it employs a common channel and a controller. Spectrum sensing data falsification (SSDF) attacks are challenging as different types of attackers use them. To address this issue, the sifting and evaluation trust management algorithm (SETM) is proposed. The necessity of computing the trust for all the secondary users (SUs) is eliminated based on the use of the first phase of the algorithm. The second phase is executed to differentiate the random attacker and the genuine SUs. This reduces the computation and overhead costs. Simulations and complexity analyses have been performed to prove the efficiency and appropriateness of the proposed algorithm for combating SSDF attacks.

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Sensor Selection for Cooperative Spectrum Sensing in Multiantenna Sensor Networks Based on Convex Optimization and Genetic Algorithm

IEEE Sensors Journal ◽

10.1109/jsen.2016.2535862 ◽

2016 ◽

Vol 16 (10) ◽

pp. 3486-3487 ◽

Cited By ~ 16

Author(s):

Seyed Hani Hojjati ◽

Ataollah Ebrahimzadeh ◽

Maryam Najimi ◽

Ali Reihanian

Keyword(s):

Genetic Algorithm ◽

Sensor Networks ◽

Convex Optimization ◽

Spectrum Sensing ◽

Cooperative Spectrum Sensing ◽

Sensor Selection ◽

Selection For

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Cooperative Spectrum Sensing Based on HML and Vector Quantization for Cognitive Radio Networks

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i2.20.16728 ◽

2018 ◽

Vol 7 (2.20) ◽

pp. 335

Author(s):

Shweta Alpna ◽

Amrit Mukherjee ◽

Amlan Datta

Keyword(s):

Communication Network ◽

Cognitive Radio ◽

Real Time ◽

Spectrum Sensing ◽

Vector Quantization ◽

Cooperative Spectrum Sensing ◽

Radio Networks ◽

Secondary Users ◽

The Real ◽

Novel Technique

The proposed work illustrates a novel technique for cooperative spectrum sensing in a cognitive radio (CR) network. The work includes an approach of identifying secondary users (SUs) based on Hierarchical Maximum Likelihood (HML) technique followed by Vector Quantization. Initially, the arrangement of the SUs are been observed using HML with respect to a spatial domain and then the active SUs among them are identified using VQ. The approach will not only save the energy, but the decision of the real-time and dynamic cooperative communication network becomes more accurate as we can predict the behavior of SUs movement and spectrum sensing by each individual SU at that particular place. The results and simulations of the real-time experiment justifies with the proposed approach.

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Deep Cooperative Spectrum Sensing Utilizing Recurrent Convolutional Neural Networks

10.21203/rs.3.rs-22343/v1 ◽

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.

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Cooperative Full-Duplex Physical and MAC Layer Design in Asynchronous Cognitive Networks

Wireless Communications and Mobile Computing ◽

10.1155/2017/8491920 ◽

2017 ◽

Vol 2017 ◽

pp. 1-14 ◽

Cited By ~ 3

Author(s):

Teddy Febrianto ◽

Jiancao Hou ◽

Mohammad Shikh-Bahaei

Keyword(s):

Spectrum Sensing ◽

Cooperative Spectrum Sensing ◽

Mac Protocol ◽

Cognitive Networks ◽

Full Duplex ◽

Mac Layer ◽

Average Throughput ◽

Secondary Users ◽

Optimum Parameters ◽

Trade Offs

In asynchronous cognitive networks (CNs), where there is no synchronization between primary users (PUs) and secondary users (SUs), spectrum sensing becomes a challenging task. By combining cooperative spectrum sensing and full-duplex (FD) communications in asynchronous CNs, this paper demonstrates improvements in terms of the average throughput of both PUs and SUs for particular transmission schemes. The average throughputs are derived for SUs and PUs under different FD schemes, levels of residual self-interference, and number of cooperative SUs. In particular, we consider two types of FD schemes, namely, FD transmit-sense-reception (FDr) and FD transmit-sense (FDs). FDr allows SUs to transmit and receive data simultaneously, whereas, in FDs, the SUs continuously sense the channel during the transmission time. This paper shows the respective trade-offs and obtains the optimal scheme based on cooperative FD spectrum sensing. In addition, SUs’ average throughput is analyzed under different primary channel utilization and multichannel sensing schemes. Finally, new FD MAC protocol design is proposed and analyzed for FD cooperative spectrum sensing. We found optimum parameters for our proposed MAC protocol to achieve higher average throughput in certain applications.

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