NDLI: A joint optimization of transmission mode selection and resource allocation for cognitive relay networks

Content Provider	IEEE Xplore Digital Library
Author	Hao Chen Pinyi Ren Li Sun Qinghe Du
Copyright Year	2013
Description	Author affiliation: Dept. of Inf. & Commun. Eng., Xi'an Jiaotong Univ., Xi'an, China (Hao Chen; Pinyi Ren; Li Sun; Qinghe Du)
Abstract	Cognitive Radio has been widely regarded as an effective way to improve the spectrum utilization. In Cognitive Radio Networks (CRN), the heterogeneity of spectrum availability often leads to link interruptions among Secondary Users (SUs). By deploying relay nodes, the link interruption problem can be effectively mitigated since relay nodes bring more freedoms for the system optimization. By jointly exploiting the multi-dimensional optimization flexibilities, including transmission mode selection, relay selection, and channel allocation, we in this paper propose a framework towards minimizing the outage percentage of SUs in cognitive relay networks. In particular, we formulate a combinatorial optimization problem to achieve this goal, which is then transformed into a max-matching problem in the Graph Theory. Using the Hungary algorithm, the optimal solution to this problem is obtained with a polynomial computational complexity. Simulation results show that by combining advantages of multiple transmission modes, including direct transmission, amplify-and-forward, and decode-and-forward, our proposed joint transmission mode selection and resource allocation strategy can significantly reduce the occurrences of link interruptions in cognitive radio networks.
Starting Page	2852
Ending Page	2856
File Size	640315
Page Count	5
File Format	PDF
ISBN	9781467331227
ISSN	15503607
DOI	10.1109/ICC.2013.6654973
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-09
Publisher Place	Hungary
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cognitive radio
Content Type	Text
Resource Type	Article

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