能量采集认知无线电的量子蝙蝠最优合作策略

doi:10.11959/j.issn.1000-436x.2018149

Abstract

Abstract:

In order to reduce energy consumption and improve spectral efficiency of the cognitive relay wireless communication system in 5G network,an optimal cooperative transmission strategy of information and energy was designed for cognitive relay radio with wireless energy harvesting.For the proposed optimal cooperative strategy,the maximal throughput formula and outage probability of secondary user were deduced.In order to resolve the derived maximum throughput equation,a quantum bat algorithm which was based on the optimization mechanism of quantum computing and bat algorithm was designed to solve the deduced equation,and the optimal cooperative transmission scheme for information and energy could be obtained.Simulation results show that the proposed optimal cooperative strategy not only can meet the information transfer demand of primary user,but also can realize the energy self-supply of the secondary user system and improve the communication quality of the secondary user.The proposed optimal cooperative strategy has a better performance than the cooperative strategy of existing cognitive relay radio for different simulation scenarios.

Key words: cognitive relay radio, energy harvesting, cooperative strategy, quantum bat algorithm, 5G network

CLC Number:

TN914.34

Hongyuan GAO,Yanan DU,Shibo ZHANG,Dandan LIU. Optimal cooperative strategy based on quantum bat for cognitive radio of energy harvesting[J]. Journal on Communications, 2018, 39(9): 10-19.

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[1]	ZHENG G , HO Z , JORSWIECK E ,et al. Information and energy cooperation in cognitive radio networks[J]. IEEE Transactions on Signal Processing, 2014,62(9): 2290-2303.
[2]	BI S Z , HO C K , ZHANG R . Wireless powered communication:opportunities and challenges[J]. IEEE Communications Magazine, 2015,53(4): 117-125.
[3]	谢振威, 朱琦 . 基于能量协作的认知能量采集网络功率分配算法[J]. 通信学报, 2017,38(9): 176-184.
	XIE Z W , ZHU Q . Power allocation algorithm for cognitive radio energy harvesting networks based on energy cooperation[J]. Journal on Communications, 2017,38(9): 176-184.
[4]	LIU Y W , MOUSAVIFAR S A , DENG Y S ,et al. Wireless energy harvesting in a cognitive relay network[J]. IEEE Transactions on Wireless Communications, 2016,15(4): 2498-2508.
[5]	谢显中, 罗莹, 严可 ,等. 认知无线电网络中四维资源协作的研究现状与未来方向[J]. 通信学报, 2018,39(2): 149-163.
	XIE X Z , LUO Y , YAN K ,et al. Recent advances and future challenges of four key resources cooperation in cognitive radio network[J]. Journal on Communications, 2018,39(2): 149-163.
[6]	ZHAI C , LIU J , ZHENG L N . Cooperative spectrum sharing with wireless energy harvesting in cognitive radio networks[J]. IEEE Transactions on Vehicular Technology, 2016,65(7): 5303-5316.
[7]	BHOWMICK A , ROY S D , KUNDU S . Throughput of a cognitive radio network with energy-harvesting based on primary user signal[J]. IEEE Wireless Communications Letters, 2016,5(2): 136-139.
[8]	刘建平, 金顺福, 王宝帅 . 基于排队模型的混合overlay/underlay频谱共享优化策略研究[J]. 通信学报, 2017,38(9): 55-64.
	LIU J P , JIN S F , WANG B S . Study on optimization strategy for hybrid underlay/overlay spectrum sharing based on queuing model[J]. Journal on Communications, 2017,38(9): 55-64.
[9]	KRIKIDIS I , LANEMAN J N , THOMPSON J S ,et al. Protocol design and throughput analysis for multi-user cognitive cooperative systems[J]. IEEE Transaction on Wireless Communications, 2009,8(9): 4740-4751.
[10]	NASIR A , ZHOU X Y , DURRANI S ,et al. Relaying protocols for wireless energy harvesting and information processing[J]. IEEE Transactions on Wireless Communications, 2013,12(7): 3622-3636.
[11]	SANKET S K , ADRISH B . Secure communication via a wireless energy harvesting untrusted relay[J]. IEEE Transactions on Vehicular Technology, 2017,66(3): 2199-2213.
[12]	ZHONG W , CHEN G , JIN S ,et al. Relay selection and discrete power control for cognitive relay networks via potential game[J]. IEEE Transactions on Signal Processing, 2014,62(20): 5411-5424.
[13]	LIU Y , MOUSAVIFAR S A , DENG Y ,et al. Wireless energy harvesting in a cognitive relay network[J]. IEEE Transactions on Wireless Communications, 2016,15(4): 2498-2508.
[14]	PRADHA J J , KALAMKAR S S , BANERJEE A . On information and energy cooperative in energy harvesting cognitive radio[C]// The 26th IEEE Annual International Symposium on Personal,Indoor,and Mobile Radio Communications. 2015: 943-948.
[15]	YIN S X , ZHANG E Q , QU Z W ,et al. Optimal cooperation strategy in cognitive radio systems with energy harvesting[J]. IEEE Transactions on Wireless Communications, 2014,13(9): 4693-4707.
[16]	MAKKI B , SVENSSON T , ERIKSSON T ,et al. On the throughput and outage probability of multi-relay networks with imperfect power amplifiers[J]. IEEE Transactions on Wireless Communications, 2015,14(9): 4994-5008.
[17]	柴争义, 王秉, 李亚伦 . 拟态物理学优化的认知无线电网络频谱分配[J]. 物理学报, 2014,63(22): 433-438.
	CHAI Z Y , WANG B , LI Y L . Spectrum allocation of cognitive radio network based on artificial physics optimization[J]. Acta Physical Sinica, 2014,63(22): 433-438.
[18]	GAO H Y , LI C W . Quantum-inspired bacterial foraging algorithm for parameter adjustment in green cognitive radio[J]. Journal of Systems Engineering and Electronics, 2015,26(5): 1-9.
[19]	GAO H Y , ZHANG S B , DU Y N ,et al. Relay selection scheme based on quantum differential evolution algorithm in relay networks[J]. KSII Transactions on Internet ＆ Information Systems, 2017,11(7): 3501-3523.
[20]	YANG X S , GANDOMI A H . Bat algorithm:a novel approach for global engineering optimization[J]. Engineering Computations:International Journal for Computer-Aided Engineering and Software, 2012,29(5): 464-483.

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