2 Citations (Scopus)

Abstract

The number of network devices continues to rise as we advance towards 6G communication systems. A new range of frequencies is allocated while the earlier resources remain underutilized. Cognitive Radio (CR) enables the dynamic spectrum management of frequencies while detecting the unoccupied bands with the aid of spectrum sensing. By adopting Deep Learning (DL) for spectrum sensing, the performance of the 6G networks can be made more robust. This paper presents a survey of several DL algorithms such as, Multilayer Perceptrons (MLPs), Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks and combination of CNNs and LSTMs that have been applied for performing spectrum sensing. The application of DL to spectrum sensing is then demonstrated by considering it as a binary classification problem. An MLP with its hyperparameters optimized by using Grid Search algorithm is proposed to classify a dataset consisting of RadioML 2018.01A and noise samples with high accuracy.

Original languageEnglish
Title of host publication2022 25th International Symposium on Wireless Personal Multimedia Communications, WPMC 2022
PublisherIEEE Computer Society
Pages480-485
Number of pages6
ISBN (Electronic)9781665473187
ISBN (Print)9781665473194
DOIs
Publication statusPublished - 20 Jan 2023
Event25th International Symposium on Wireless Personal Multimedia Communications - Herning, Denmark
Duration: 30 Oct 20222 Nov 2022
Conference number: 25

Publication series

NameInternational Symposium on Wireless Personal Multimedia Communications, WPMC
PublisherIEEE
ISSN (Print)1347-6890
ISSN (Electronic)1882-5621

Conference

Conference25th International Symposium on Wireless Personal Multimedia Communications
Abbreviated titleWPMC 2022
Country/TerritoryDenmark
CityHerning
Period30/10/222/11/22

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