Work place: B.M.S. College of Engineering, Bengaluru, Karnataka 560019, India
Research Interests: Wireless Networks
Nethravathi H. M. is a research scholar in the Department of ECE, BMSCE, VTU. She received the B.E degree from the VTU, in Electronics and Communication Engineering, 2008 and the M. Tech degree from the VTU, in 2012, in Digital communication Engineering. She is currently pursuing the Ph. D degree with the Electronics and Communication, BMSCE, VTU. Her research interests include Wireless and Mobile networks, Adhoc networks, Wireless Sensor networks. Email: email@example.com
DOI: https://doi.org/10.5815/ijcnis.2023.05.01, Pub. Date: 8 Oct. 2023
D2D (Device-to-device) communication has a major role in communication technology with resource and power allocation being a major attribute of the network. The existing method for D2D communication has several problems like slow convergence, low accuracy, etc. To overcome these, a D2D communication using distributed deep learning with a coot bird optimization algorithm has been proposed. In this work, D2D communication is combined with the Coot Bird Optimization algorithm to enhance the performance of distributed deep learning. Reducing the interference of eNB with the use of deep learning can achieve near-optimal throughput. Distributed deep learning trains the devices as a group and it works independently to reduce the training time of the devices. This model confirms the independent resource allocation with optimized power value and the least Bit Error Rate for D2D communication while sustaining the quality of services. The model is finally trained and tested successfully and is found to work for power allocation with an accuracy of 99.34%, giving the best fitness of 80%, the worst fitness value of 46%, mean value of 6.76 and 0.55 STD value showing better performance compared to the existing works.[...] Read more.
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