Joint iterative algorithm for optimal cooperative spectrum sensing in cognitive radio networks

In this paper, joint optimization of throughput and error rate via cooperative spectrum sensing in cognitive radio networks is investigated. An optimization problem is formulated, which aims to maximize the average achievable throughput of cooperating cognitive users while keeping the error rate at...

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Main Authors: Zhang, Wenjie, Yeo, Chai Kiat
Other Authors: School of Computer Engineering
Format: Article
Language:English
Published: 2013
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Online Access:https://hdl.handle.net/10356/97374
http://hdl.handle.net/10220/13149
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-973742020-05-28T07:18:03Z Joint iterative algorithm for optimal cooperative spectrum sensing in cognitive radio networks Zhang, Wenjie Yeo, Chai Kiat School of Computer Engineering DRNTU::Engineering::Computer science and engineering In this paper, joint optimization of throughput and error rate via cooperative spectrum sensing in cognitive radio networks is investigated. An optimization problem is formulated, which aims to maximize the average achievable throughput of cooperating cognitive users while keeping the error rate at a lower level. This is a multi-variable nonconvex optimization problem. Instead of solving it directly, we propose an iterative algorithm which jointly optimizes the threshold and sensing time together to decrease the effect of the error and to increase the achievable throughput. We first prove that the local error rate of the cognitive user is a convex function of energy threshold and determine a closed-form for the optimal threshold which minimizes the error rate. Then we show that the AND rule is the optimal fusion rule to maximize the achievable throughput. Furthermore we determine the least number of cooperating cognitive users that can guarantee a minimum target error rate. This initial nonconvex problem is converted into a single variable convex optimization problem which can be successfully solved by common methods e.g. Newton’s method. Simulation results illustrate the fast convergence and effectiveness of the joint iterative algorithm. 2013-08-16T03:44:32Z 2019-12-06T19:41:58Z 2013-08-16T03:44:32Z 2019-12-06T19:41:58Z 2012 2012 Journal Article Zhang, W.,& Yeo, C. K. (2012). Joint iterative algorithm for optimal cooperative spectrum sensing in cognitive radio networks. Computer Communications, 36(1), 80-89. 0140-3664 https://hdl.handle.net/10356/97374 http://hdl.handle.net/10220/13149 10.1016/j.comcom.2012.07.015 en Computer communications
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering
spellingShingle DRNTU::Engineering::Computer science and engineering
Zhang, Wenjie
Yeo, Chai Kiat
Joint iterative algorithm for optimal cooperative spectrum sensing in cognitive radio networks
description In this paper, joint optimization of throughput and error rate via cooperative spectrum sensing in cognitive radio networks is investigated. An optimization problem is formulated, which aims to maximize the average achievable throughput of cooperating cognitive users while keeping the error rate at a lower level. This is a multi-variable nonconvex optimization problem. Instead of solving it directly, we propose an iterative algorithm which jointly optimizes the threshold and sensing time together to decrease the effect of the error and to increase the achievable throughput. We first prove that the local error rate of the cognitive user is a convex function of energy threshold and determine a closed-form for the optimal threshold which minimizes the error rate. Then we show that the AND rule is the optimal fusion rule to maximize the achievable throughput. Furthermore we determine the least number of cooperating cognitive users that can guarantee a minimum target error rate. This initial nonconvex problem is converted into a single variable convex optimization problem which can be successfully solved by common methods e.g. Newton’s method. Simulation results illustrate the fast convergence and effectiveness of the joint iterative algorithm.
author2 School of Computer Engineering
author_facet School of Computer Engineering
Zhang, Wenjie
Yeo, Chai Kiat
format Article
author Zhang, Wenjie
Yeo, Chai Kiat
author_sort Zhang, Wenjie
title Joint iterative algorithm for optimal cooperative spectrum sensing in cognitive radio networks
title_short Joint iterative algorithm for optimal cooperative spectrum sensing in cognitive radio networks
title_full Joint iterative algorithm for optimal cooperative spectrum sensing in cognitive radio networks
title_fullStr Joint iterative algorithm for optimal cooperative spectrum sensing in cognitive radio networks
title_full_unstemmed Joint iterative algorithm for optimal cooperative spectrum sensing in cognitive radio networks
title_sort joint iterative algorithm for optimal cooperative spectrum sensing in cognitive radio networks
publishDate 2013
url https://hdl.handle.net/10356/97374
http://hdl.handle.net/10220/13149
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