基于遗传算法的认知无线网络QoS感知自适应子载波分配

D. Patil, V. Wankhede, V. Wadhai
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引用次数: 1

摘要

提出了一种基于工作参数重构的认知无线网络自适应子载波分配方案。提出了一种qos意识频谱决策框架,其中频谱带是通过考虑应用需求和频谱带的动态特性来确定的。针对crn中认知无线电(CR)用户的子载波分配和功率分配问题,提出了一种新的子载波分配算法,以满足不同的性能目标。采用比例资源算法和遗传算法对工作频率参数进行修改。研究具有不等式约束的多目标优化问题。此外,提出了一种基于遗传算法的动态子载波分配方案,根据时变的CR网络容量自适应地确定频段。该算法的目标是从动态频谱管理(DSM)的角度出发,在带宽约束下,实现各子载波的最大数据速率、网络整体吞吐量和满足用户数量最大化,保证服务质量(QoS)要求。此外,它还确定了最佳可用信道。
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Genetic Algorithm Based QoS Aware Adaptive Subcarrier Allocation in Cognitive Radio Networks
In this paper, an adaptive subcarrier allocation scheme with reconfiguration of operating parameters for Cognitive Radio Networks (CRN) is presented. A QoS-conscious spectrum decision frame work is projected, where spectrum bands are determined by considering the application requirements as well as the dynamic nature of the spectrum bands. The novel subcarrier allocation algorithm is developed to fulfill different performance objective as a solution for subcarrier allocation and power allocation problem for Cognitive Radio (CR) users in CRNs. It employs operating frequency parameter modification using Proportional Resource Algorithm and Genetic Algorithm (GA). The multi objective optimization problem with equality and inequality constraint is considered. Moreover, a dynamic subcarrier allocations scheme is developed based on GA to decide on the spectrum bands adaptively dependent on the time-varying CR network capacity. The proposed algorithm targets to achieve maximum data rate for each subcarrier, maximize the overall network throughput and maximize the number of satisfied user under the constraints of bandwidth and guarantee Quality of Service (QoS) requirement from dynamic spectrum management (DSM) perspective. Moreover, it determines the best available channel.
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