摘要
新的无线网络技术设备的发展使得多种无线技术共存的异构无线网络渐渐地替代了单一技术构成的同构无线网络。为了获得高覆盖、低成本与低辐射的室内异构无线网络,提出了一个遗传算法与类粒子群算法相结合的混合算法。这个算法具备遗传算法搜索的广度及类离子群算法搜索的深度,并且避免了过早收敛于局部。算法被应用于多目标异构无线网络的规划中,仿真结果证明,这个混合算法能有效地实现多目标的无线网络规划方案的优化。
The requirement of information interaction promotes the expansion of wireless networks. In the same period of time,development of new wireless network technologies and equipments results in a variety of wireless network architectures. As the result,the homogeneous network,which is composed of a single wireless network,is gradually replaced by the heterogeneous wireless network. This paper presented a hybrid algorithm combined the genetic algorithm with the quasi particle swarm algorithm. Improved genetic algorithm was used to search the breadth and depth,it also could avoid the premature convergence to the local optimal. The presented algorithm optimized the multi-objective heterogeneous wireless network planning. The simulation results show that the hybrid algorithm can effectively achieve the multi-objective optimization( high coverage,low energy consumption and low exposure level) of the wireless network planning solution.
作者
刘宁
秦志光
David Plets
Wout Joseph
Liu Ning;Qin Zhiguang(School of Computer Science & Engineering, University Electronic Science & Technology of China, Chengdu 611131 , China;WiCa, Dept,of Information Technology, Ghent University/iMinds, Ghent B-9050 , Belgium)
出处
《计算机应用研究》
CSCD
北大核心
2016年第9期2774-2777,共4页
Application Research of Computers
基金
四川省科技支撑计划资助项目(2013GZ0022)
新疆维吾尔自治区科技支疆计划资助项目(201491121)
关键词
室内无线网络规划
优化算法
异构无线网络
多目标优化
indoor wireless network planning
optimization algorithm
heterogeneous wireless network
multi-objective optimization
