JOURNAL ARTICLE

Opportunistic Spectrum Access with Two Channel Sensing in Cognitive Radio Networks

Jin LaiEryk DutkiewiczRen Ping LiuRein Vesilo

Year: 2014 Journal:   IEEE Transactions on Mobile Computing Vol: 14 (1)Pages: 126-138   Publisher: IEEE Computer Society

Abstract

Efficient discovery and effective sharing of spectrum opportunities are the most challenging issues in a multi-channel cognitive radio network (CRN) with multiple secondary users (SUs). In this paper, we propose a novel spectrum sensing and access protocol in CRNs where SUs are allowed to sequentially sense two channels in a single time slot and are coordinated to access the potentially unused channels. The proposed protocol is formulated as a channel selection problem coupled with a channel assignment problem. We subsequently investigate the myopic sensing policy and propose a Markov chain-based greedy channel assignment scheme (MCGA) to maximize the expected total SU throughput. Moreover, we extend our proposal to the scenario with imperfect spectrum sensing and obtain the optimal sensing time to enhance the performance improvement by considering spectrum sensing and spectrum access in a joint manner. Finally, we evaluate the performance of our proposal in a saturated network. Numerical and simulation results demonstrate that compared to the existing work, our approach can achieve significant performance improvements in SU throughput.

Keywords:
Computer science Cognitive radio Throughput Computer network Channel (broadcasting) Markov chain Greedy algorithm Distributed computing Wireless Telecommunications Algorithm

Metrics

36
Cited By
5.88
FWCI (Field Weighted Citation Impact)
25
Refs
0.96
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cognitive Radio Networks and Spectrum Sensing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Advanced MIMO Systems Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Advanced Queuing Theory Analysis
Social Sciences →  Business, Management and Accounting →  Management Information Systems
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