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联合多分组接收和模糊逻辑控制功率策略
引用本文:韩江洪,胡松华,刘 斌,陈 振,刘 磊.联合多分组接收和模糊逻辑控制功率策略[J].通信学报,2015,36(2):11-19.
作者姓名:韩江洪  胡松华  刘 斌  陈 振  刘 磊
作者单位:1. 合肥工业大学 计算机与信息学院,安徽 合肥 230009;2. 河南理工大学 电气工程与自动化学院,河南 焦作 454000
基金项目:国家自然科学基金资助项目(61370088);高等学校博士学科点专项科研基金资助项目(20100111110004)
摘    要:针对无线网络节约能耗的要求,提出了一种联合多分组接收和模糊逻辑控制功率策略,采用串行干扰消除法,根据无线节点的传输功率等级,将功率等级划分为多分组接收能够正常解码的功率等级,并以任一无线节点到邻接节点的距离、邻接节点的个数和无线节点的剩余能耗为模糊逻辑控制的输入参数来控制各无线节点的功率选择。仿真结果表明,与现有的几种经典的基于功率控制的串行干扰消除算法方案相比,联合多分组接收和模糊逻辑控制功率策略的无线网络具有更大的有效吞吐量及更长的生存时间。

关 键 词:多分组接收  串行干扰消除  网络优化  模糊逻辑控制

Power control strategy with joint of multi-packet reception and fuzzy logic control
HAN Jiang-hong;HU Song-hua;LIU Bin;CHEN Zhen;LIU Lei.Power control strategy with joint of multi-packet reception and fuzzy logic control[J].Journal on Communications,2015,36(2):11-19.
Authors:HAN Jiang-hong;HU Song-hua;LIU Bin;CHEN Zhen;LIU Lei
Affiliation:1. School of Computer &Information,Hefei University of Technology,Hefei 230009,China;2. School of Electrical Engineering &Automation,Henan Polytechnic University,Jiaozuo 454000,China
Abstract:In order to meet the needs of energy saving in wireless networks, a power control strategy with joint of multi-packet reception and fuzzy logic was proposed. Firstly, based on the power control with successive interference cancellation (SIC), transmission power was divided into several decodable power levels. Secondly, fuzzy logic control algorithm was adopted to select the optimal transmission power for SIC. In addition, three parameters were designed as fuzzy logic control inputs for power selection, which were the distance between transmitters and receivers, the number of neighboring nodes and the residual energy of transmitters. Simulation results show that power control strategy with joint of multi-packet reception and fuzzy logic control not only betters average network throughput than other power control strategy for SIC, but also saves more energy so that the network lifecycle would be significantly extended.
Keywords:multi-packet reception  successive interference cancellation  network optimization  fuzzy logic control
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