Spectrum Availability Prediction for Cognitive Radio Networks
K. Annapurna1, T. Hymavathi2, B. Seetha Ramanjaneyulu3

1K. Annapurna, Department of ECE, VFSTR, Guntur (Andhra Pradesh), India.
2T. Hymavathi, Department of ECE, VFSTR, Guntur (Andhra Pradesh), India.
3B. Seetha Ramanjaneyulu, Department of ECE, VFSTR, Guntur (Andhra Pradesh), India.
Manuscript received on 13 February 2019 | Revised Manuscript received on 04 March 2019 | Manuscript Published on 08 June 2019 | PP: 257-260 | Volume-7 Issue-5S4, February 2019 | Retrieval Number: E10510275S419/19©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Cognitive radio networks enable the secondary users to make use of the frequency spectrum of primary users in the absence of the latter. To make this mechanism possible, secondary users have to sense the spectrum to find vacant channels to occupy them as well as to vacate the occupied channels when their primary users come back. ANFIS based spectrum prediction is proposed in this work to improve the spectrum utilization, reduce interference to primary users, enhance quality of service to secondary users and save sensing energy and time. Comparison of predicted data with actual data shows that the predicted occupancy of spectrum is close to the actual occupancy.
Keywords: Spectrum Prediction, ANFIS, Cognitive Radio Networks, Opportunistic Channel Access.
Scope of the Article: Cognitive Radio Networks