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Energy-Efficient Sensor Scheduling Algorithm in Cognitive Radio Networks Employing Heterogeneous Sensors

Liu, X, Evans, BG and Moessner, K (2015) Energy-Efficient Sensor Scheduling Algorithm in Cognitive Radio Networks Employing Heterogeneous Sensors IEEE Transactions on Vehicular Technology, 64 (3). pp. 1243-1249.

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Abstract

We consider, in this paper, the maximization of throughput in a dense network of collaborative cognitive radio (CR) sensors with limited energy supply. In our case, the sensors are mixed varieties (heterogeneous) and are battery powered. We propose an ant colony-based energy-efficient sensor scheduling algorithm (ACO-ESSP) to optimally schedule the activities of the sensors to provide the required sensing performance and increase the overall secondary system throughput. The proposed algorithm is an improved version of the conventional ant colony optimization (ACO) algorithm, specifically tailored to the formulated sensor scheduling problem. We also use a more realistic sensor energy consumption model and consider CR networks employing heterogeneous sensors (CRNHSs). Simulations demonstrate that our approach improves the system throughput efficiently and effectively compared with other algorithms.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Liu, X
Evans, BGB.Evans@surrey.ac.uk
Moessner, Kk.moessner@surrey.ac.uk
Date : 1 March 2015
Funders : Engineering and Physical Sciences Research Council (EPSRC)
DOI : 10.1109/TVT.2013.2290031
Copyright Disclaimer : © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords : Collaborative spectrum sensing; Sensor scheduling problem; Throughput maximization; Ant colony optimization (ACO); Throughput; Sensors; Energy consumption; Batteries; Scheduling algorithms; Cascading style sheets; Greedy algorithms
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 13:35
Last Modified : 14 Mar 2019 11:09
URI: http://epubs.surrey.ac.uk/id/eprint/839739

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