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An Improved Centralized Cognitive Radio Network Spectrum Allocation Algorithm Based on the Allocation Sequence

机译:基于分配序列的集中式认知无线网络频谱分配改进算法

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The demand of the wireless communications service is increasing in recent years, and the demand of the wireless communication rate is increasing too. However, the static spectrum allocation mechanism results in lots of free spectrum resources in space, and the spectrum is wasted. The cognitive radio technology with intelligent searching and efficient utilization of the idle spectrum resources just provides the opportunity to use the free spectrum resources. Thus, the spectrum allocation technology of the cognitive radio has also been more and more broadly concerned. In order to avoid the interference, a mathematical model of spectrum allocation for cognitive radio spectrum allocation algorithm is established through a graph theory. The spectrum allocation algorithms with different allocation objectives based on graph theory are studied according to the different network structures. After the basic ideas and allocation processes of these algorithms are described, a centralized network spectrum allocation algorithm based on the allocation sequence is proposed. Simulation results show that the improved algorithm can significantly reduce the time overhead and can have better fairness compared with other existing Collaborative-Max-Sum-Reward (CSUM), Collaborative-Max-Min-Reward (CMIN), and Collaborative-Max-Proportional-Fair (CFAIR) algorithms under the same design criterion.
机译:近年来,无线通信服务的需求在增加,并且无线通信速率的需求也在增加。但是,静态频谱分配机制导致空间中有大量自由频谱资源,从而浪费了频谱。具有智能搜索功能和对空闲频谱资源的有效利用的认知无线电技术仅提供了使用自由频谱资源的机会。因此,认知无线电的频谱分配技术也越来越受到关注。为了避免干扰,通过图论建立了认知无线电频谱分配算法的频谱分配数学模型。针对不同的网络结构,研究了基于图论的具有不同分配目标的频谱分配算法。在描述了这些算法的基本思想和分配过程之后,提出了一种基于分配序列的集中式网络频谱分配算法。仿真结果表明,与其他现有的“协作最大-最大-奖励”(CSUM),“协作最大-最大-奖励”(CMIN)和“协作最大-最大”比例相比,改进后的算法可以显着减少时间开销并具有更好的公平性。相同设计标准下的-Fair(CFAIR)算法。

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