Cooperative Soft Fusion for HMM based Spectrum Occupancy Prediction

Eltom, H, Sithamparanathan, K, Liang, Y and Evans, R 2018, 'Cooperative Soft Fusion for HMM based Spectrum Occupancy Prediction', IEEE Communications Letters, vol. 22, no. 10, pp. 2144-2147.


Document type: Journal Article
Collection: Journal Articles

Title Cooperative Soft Fusion for HMM based Spectrum Occupancy Prediction
Author(s) Eltom, H
Sithamparanathan, K
Liang, Y
Evans, R
Year 2018
Journal name IEEE Communications Letters
Volume number 22
Issue number 10
Start page 2144
End page 2147
Total pages 4
Publisher IEEE
Abstract Spectrum occupancy prediction allows cognitive radio secondary users to exploit temporal spectrum opportunities one step-ahead. Temporal correlations in spectrum sensing measurements can be utilised to predict primary user activity patterns. Where applicable, cooperative spectrum prediction has the potential to improve prediction accuracy compared to single user (local) spectrum prediction. This paper presents the concept and methods for soft fusion based cooperative spectrum occupancy prediction. The proposed methods were simulated and the results show significant improvement in prediction error over local, and hard fusion based spectrum prediction.
Subject Networking and Communications
Signal Processing
Wireless Communications
Keyword(s) cognitive radio
cooperative spectrum prediction
dynamic spectrum access
Erbium
Hidden Markov models
Markov processes
Predictive models
Probability
Sensors
Signal to noise ratio
spectrum occupancy
DOI - identifier 10.1109/LCOMM.2018.2861008
Copyright notice © 2018 IEEE
ISSN 1089-7798
Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 1 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 0 times in Scopus Article
Altmetric details:
Access Statistics: 5 Abstract Views  -  Detailed Statistics
Created: Thu, 06 Dec 2018, 10:39:00 EST by Catalyst Administrator
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us