Application of Quantum-Inspired Evolutionary Algorithm to Improve the Beampattern of Collaborative Beamforming in Wireless Sensor Networks
碩士 === 國立高雄師範大學 === 光電與通訊工程學系 === 103 === Collaborative beamforming (CB), which forms a virtual antenna array from a subset number of distributed wireless nodes in wireless sensor networks,can increase the transmission range and improve energy efficiency. However, due to the distributed nature of wi...
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ndltd-TW-103NKNU56520042016-12-22T04:19:05Z http://ndltd.ncl.edu.tw/handle/51358913307742443264 Application of Quantum-Inspired Evolutionary Algorithm to Improve the Beampattern of Collaborative Beamforming in Wireless Sensor Networks 以量子演算法優化無線感測網路中合作波束成型技術 陳柏宇 碩士 國立高雄師範大學 光電與通訊工程學系 103 Collaborative beamforming (CB), which forms a virtual antenna array from a subset number of distributed wireless nodes in wireless sensor networks,can increase the transmission range and improve energy efficiency. However, due to the distributed nature of wireless sensor nodes, it is necessary to select appropriate cooperating nodes for CB to achieve a desired beampattern. In this paper, we propose a novel algorithm that uses quantum-inspired evolutionary algorithm (QEA) to search over different wireless sensor node combinations. Simulation results show that the proposed QEA-based node selection method performs better than the other existing algorithms, such as genetic algorithms. 陳榮杰 博士 2015 學位論文 ; thesis 35 zh-TW |
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碩士 === 國立高雄師範大學 === 光電與通訊工程學系 === 103 === Collaborative beamforming (CB), which forms a virtual antenna array from a subset number of distributed wireless nodes in wireless sensor networks,can increase the transmission range and improve energy efficiency.
However, due to the distributed nature of wireless sensor nodes, it is necessary to select appropriate cooperating nodes for CB to achieve a desired beampattern.
In this paper, we propose a novel algorithm that uses quantum-inspired evolutionary algorithm (QEA) to search over different wireless sensor node combinations.
Simulation results show that the proposed QEA-based node selection method performs better than the other existing algorithms, such as genetic algorithms.
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陳榮杰 博士 |
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陳榮杰 博士 陳柏宇 |
author |
陳柏宇 |
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陳柏宇 Application of Quantum-Inspired Evolutionary Algorithm to Improve the Beampattern of Collaborative Beamforming in Wireless Sensor Networks |
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陳柏宇 |
title |
Application of Quantum-Inspired Evolutionary Algorithm to Improve the Beampattern of Collaborative Beamforming in Wireless Sensor Networks |
title_short |
Application of Quantum-Inspired Evolutionary Algorithm to Improve the Beampattern of Collaborative Beamforming in Wireless Sensor Networks |
title_full |
Application of Quantum-Inspired Evolutionary Algorithm to Improve the Beampattern of Collaborative Beamforming in Wireless Sensor Networks |
title_fullStr |
Application of Quantum-Inspired Evolutionary Algorithm to Improve the Beampattern of Collaborative Beamforming in Wireless Sensor Networks |
title_full_unstemmed |
Application of Quantum-Inspired Evolutionary Algorithm to Improve the Beampattern of Collaborative Beamforming in Wireless Sensor Networks |
title_sort |
application of quantum-inspired evolutionary algorithm to improve the beampattern of collaborative beamforming in wireless sensor networks |
publishDate |
2015 |
url |
http://ndltd.ncl.edu.tw/handle/51358913307742443264 |
work_keys_str_mv |
AT chénbǎiyǔ applicationofquantuminspiredevolutionaryalgorithmtoimprovethebeampatternofcollaborativebeamforminginwirelesssensornetworks AT chénbǎiyǔ yǐliàngziyǎnsuànfǎyōuhuàwúxiàngǎncèwǎnglùzhōnghézuòbōshùchéngxíngjìshù |
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1718405334258679808 |