Title: Deep belief network with FOA-based cooperative spectrum sensing in cognitive radio network

Authors: Siva Reddy Sonti; Mutchakayala Siva Ganga Prasad

Addresses: Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Vijayawada, Andhra Pradesh, 520002, India ' Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Vijayawada, Andhra Pradesh, 520002, India

Abstract: The artificial neural network (ANN) is proposed to the cooperative spectrum sensing (CSS) at CR network. ANN has the drawback that the training of ANN with many hidden layers on large amount of data can affect the performance of the network and optimisation of ANN parameters is a challenging task. To overcome the above drawbacks, the deep belief network (DBN) and fruit fly optimisation algorithm (FOA) are employed. The DBN has four parameters on learning step: learning rate, weight decay, penalty parameter, number of hidden units. These parameters should be properly selected for the proper functioning of DBN. Tuning of these parameters is taken into an optimisation issue and it is addressed by FOA. The proposed method has three steps: training, validation and testing. The metrics used for the performance evaluation are accuracy, false alarm rate and loss detection.

Keywords: cognitive radio; CR; cooperative spectrum sensing; CSS; deep belief network; DBN; fruit fly optimisation algorithm; FOA.

DOI: 10.1504/IJCNDS.2021.118128

International Journal of Communication Networks and Distributed Systems, 2021 Vol.27 No.3, pp.323 - 347

Received: 20 Nov 2020
Accepted: 06 Mar 2021
Published online: 12 Oct 2021 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article