基于粒子群算法的无线信道资源分配算法研究

计算机科学 ›› 2017, Vol. 44 ›› Issue (10): 109-112.doi: 10.11896/j.issn.1002-137X.2017.10.021

基于粒子群算法的无线信道资源分配算法研究

王晓楠,巨永锋,高婷,张福泉

长安大学电子与控制工程学院西安710064,长安大学电子与控制工程学院西安710064,长安大学电子与控制工程学院西安710064,北京理工大学软件学院北京100082

出版日期:2018-12-01 发布日期:2018-12-01
基金资助:
本文受国家教育部博士点基金(20121101110037,9140A04010114BQ010xx),国家自然科学基金(60806043)资助

Research on Wireless Channel Resource Allocation Algorithm Based on Particle Swarm Optimization Algorithm

WANG Xiao-nan, JU Yong-feng, GAO Ting and ZHANG Fu-quan

Online:2018-12-01 Published:2018-12-01

摘要/Abstract

摘要： 为了最大化多媒体无线信道资源分配的网络效用,提出了一种新的基于粒子群算法的信道时间分配算法。该算法能够优化分配给网络内每个设备的时间,以便为每位网络用户提供最优化的服务质量(QoS)。所提算法结合了多样性增加函数以及基于个体最优值的学习方法,并基于自适应粒子群算法进行了改进,在持续增强QoS的同时加快了收敛速度。在多达40个设备的千兆网络环境内对所提算法进行了测试。实验结果表明,提出的算法能够大大提升资源分配能力,尤其是在网络规模较大的情况下。

关键词: 无线信道,粒子群算法,资源分配,自适应QoS

Abstract: In order to maximize the network utility of multimedia wireless channel resource allocation,a new channel time allocation algorithm based on particle swarm optimization algorithm was proposed.The algorithm can optimize the time allocated to each device in the network so as to maximize the quality of service (QoS) for each network user.The proposed algorithm combines the diversity increasing function and the learning method based on the individual optimal value,and improves the algorithm based on adaptive particle swarm optimization algorithm.The convergence speed of the algorithm increases at the same time of the continuous enhancement of QoS.The proposed algorithm is tested in a gigabit network environment of up to 40 devices.Experimental results show that the proposed algorithm can greatly improve the resource allocation capability,especially in the case of large network size.

Key words: Wireless channel,Particle swarm optimization algorithm,Resource allocation,Adaptive QoS

王晓楠,巨永锋,高婷,张福泉. 基于粒子群算法的无线信道资源分配算法研究[J]. 计算机科学, 2017, 44(10): 109-112. https://doi.org/10.11896/j.issn.1002-137X.2017.10.021

WANG Xiao-nan, JU Yong-feng, GAO Ting and ZHANG Fu-quan. Research on Wireless Channel Resource Allocation Algorithm Based on Particle Swarm Optimization Algorithm[J]. Computer Science, 2017, 44(10): 109-112. https://doi.org/10.11896/j.issn.1002-137X.2017.10.021

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