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题名: A genetic approach on cross-layer optimization for cognitive radio wireless mesh network under SINR model
作者: Jia J(贾杰) ; Wang XW(王兴伟) ; Chen J(陈剑)
作者部门: 工业控制网络与系统研究室
关键词: Wireless mesh network ; Throughput optimization ; Channel allocation ; Power control ; Route selection ; Genetic algorithm
刊名: AD HOC NETWORKS
ISSN号: 1570-8705
出版日期: 2015
卷号: 27, 页码:57-67
收录类别: SCI ; EI
产权排序: 1
项目资助者: National Natural Science Foundation of China [61173153, 61402096, 60903159] ; National Science Foundation for Distinguished Young Scholars of China [61225012, 71325002] ; Fundamental Research Funds for the Central Universities [N130504007, N110404014, N110318001, N110204003, N120104001] ; Specialized Research Fund of the Doctoral Program of Higher Education for the Priority Development Areas [20120042130003] ; China MOE ; China Mobile Joint Research Foundation [MCM20130391]
摘要: Due to the limited spectrum resources and the differences of link loads, how to obtain maximum network throughput through cross-layer design under signal-to-interference-and-noise ratio (SINR) model is recognized as a fundamental but hard problem. For this reason, the throughput maximization problem jointly with power control, channel allocation and routing under SINR model is researched. First, by formulating the optimization model and digging up its special structure, we show that the throughput maximization problem can be decomposed into two sub-problems: a channel allocation and power control sub-problem at the link-physical layer, and a throughput optimization sub-problem at the network layer. As to the link-physical layer sub-problem, since the joint optimization on channel allocation and power control is NP hard, we apply genetic algorithm for searching the optimal solution. As to the network layer sub-problem, we use linear programming technique for throughput optimization. To reflect the interplay property among these three layers, the fitness of each individual in the genetic algorithm is evaluated by solving the network layer sub-problem. Therefore, an effective cross-layer optimization framework based on genetic algorithm is obtained, which can find optimized power control, channel allocation and route selection in polynomial time. In order to enhance the convergence process during evolution, the integer based representation scheme and corresponding genetic operators are well designed with appropriate constraint control mechanisms. Extensive simulation results demonstrate that the proposed scheme obtains higher network throughput compared to the pervious works with comparable computational complexity. (C) 2014 Elsevier B.V. All rights reserved.
语种: 英语
WOS记录号: WOS:000349732400004
WOS标题词: Science & Technology ; Technology
类目[WOS]: Computer Science, Information Systems ; Telecommunications
关键词[WOS]: CHANNEL ASSIGNMENT ; POWER-CONTROL ; ALLOCATION ; ALGORITHMS ; CAPACITY ; GAME
研究领域[WOS]: Computer Science ; Telecommunications
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内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/16469
Appears in Collections:工业控制网络与系统研究室_期刊论文

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