Title
Increase the end-to-end throughput of a cognitive radio chain by considering the primary usage pattern and transmission scheduling
Abstract
In this paper, we investigated the end-to-end throughput of a chain in Cognitive Radio Networks (CRNs). We found that, the end-to-end throughput is dependant on both the primary usage patterns and the transmission scheduling scheme being used. In addition, to increase the end-to-end throughput of a Cognitive Radio (CR) chain, the scheduling scheme should be adjusted according to the primary usage patterns of the CR links in the chain. In the paper, firstly, we proposed an algorithm to approximate the achievable end-to-end throughput considering the primary usage patterns by abstraction and iteration. Then, a novel layered packets transmission scheduling scheme was proposed in attempt to realize the approximated end-to-end throughput. Finally, extensive simulations were conducted and results showed that, using proposed transmission scheduling scheme, the achievable end-to-end throughput of a CR chain is increased by considering the primary usage patterns and the final end-to-end throughput is close to the approximation.
Year
DOI
Venue
2009
10.1109/WCNC.2009.4917755
WCNC
Keywords
Field
DocType
cr link,final end-to-end throughput,approximated end-to-end throughput,scheduling scheme,end-to-end throughput,cognitive radio chain,transmission scheduling scheme,cr chain,achievable end-to-end throughput,primary usage pattern,proposed transmission scheduling scheme,space technology,approximation algorithms,cognitive radio network,cognitive radio networks,wireless communication,cognitive radio,schedules,throughput,scheduling,chromium,signal processing
Approximation algorithm,Fair-share scheduling,Scheduling (computing),Computer science,Network packet,Computer network,Real-time computing,Schedule,Maximum throughput scheduling,Throughput,Cognitive radio
Conference
Citations 
PageRank 
References 
0
0.34
8
Authors
5
Name
Order
Citations
PageRank
Guang Lei1171.44
Chunjing Hu2457.38
Wei Wang347753.58
Tao Peng4617.57
Wang Wenbo51200130.70