publication . Article . 2016

Spectrum Hole Identification in IEEE 802.22 WRAN using Unsupervised Learning

Chittaranjan Hota; V. Balaji; G. Raghurama; S. Anand;
Open Access English
  • Published: 19 Jan 2016 Journal: EAI Endorsed Transactions on Wireless Spectrum, volume 2, issue 7, pages 1-8 (issn: 2312-6620, Copyright policy)
  • Publisher: European Alliance for Innovation (EAI)
Abstract
In this paper we present a Cooperative Spectrum Sensing (CSS) algorithm for Cognitive Radios (CR) based on IEEE 802.22Wireless Regional Area Network (WRAN) standard. The core objective is to improve cooperative sensing efficiency which specifies how fast a decision can be reached in each round of cooperation (iteration) to sense an appropriate number of channels/bands (i.e. 86 channels of 7MHz bandwidth as per IEEE 802.22) within a time constraint (channel sensing time). To meet this objective, we have developed CSS algorithm using unsupervised K-means clustering classification approach. The received energy level of each Secondary User (SU) is considered as the ...
Subjects
free text keywords: Cognitive radio, Dynamic Spectrum Access, Cooperative Sensing, TV white space, Machine Learning, lcsh:Technology, lcsh:T, Speech recognition, IEEE 802.22, Pattern recognition, Unsupervised learning, Computer science, Artificial intelligence, business.industry, business
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