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Optimizing Spectrum Sensing by Using Artificial Neural Network in Cognitive Radio Sensor Networks

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Abstract

Resource allocation is most needed in the next generation of Cognitive radio networks these techniques are used to increase the Cognitive radio network’s performance. But, it is difficult to accomplish these techniques in real-time performance wireless. In this paper, a resource allocation technique based on artificial neural networks (ANN) is proposed which helps to reduce the power consumption in the network. The goal of the proposed scheme is to secure data transmission and to increase the uplink and downlink speed with less bit error rate. From the Simulation results, it can be observed that the proposed technique based on ANN is efficient in terms of the computation time related to the other resource allocation techniques. To increase the security of the data transmission in networks Location-based key management system is used. This paper is implemented by NS2.

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Authors and Affiliations

  1. Department of ECE, Francis Xavier Engineering College, Tirunelveli, India

    S. Esakki Rajavel & G. Rajakumar

  2. Department of ECE, Paavai Engineering College, Namakkal, India

    T. Aruna

  3. Department of ECE, St Mother Theresa Engineering College, Palayamkottai, India

    A. Tony Claudia

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  1. S. Esakki Rajavel
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  2. T. Aruna
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  3. G. Rajakumar
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  4. A. Tony Claudia
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Correspondence to S. Esakki Rajavel.

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Rajavel, S.E., Aruna, T., Rajakumar, G. et al. Optimizing Spectrum Sensing by Using Artificial Neural Network in Cognitive Radio Sensor Networks. Wireless Pers Commun 125, 803–817 (2022). https://doi.org/10.1007/s11277-022-09578-1

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