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QoS provisioning wireless multimedia transmission over cognitive radio networks

机译:认知无线电网络上的QoS设置无线多媒体传输

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The rapid growing of wireless multimedia applications increases the needs of spectrum resources, but today's spectrum resources have become more and more scarce and large part of the assigned spectrum is in an inefficiency usage. Cognitive Radio (CR) technologies are proposed to solve current spectrum inefficiency problems and offer users a ubiquitous wireless accessing environment, relying on dynamic spectrum allocation. However, there are two unsolved problems in previous work: 1) based on the simplified Quality of Service (QoS) uniform assumption, specific requirements of different wireless multimedia applications cannot be satisfied; 2) aiming at single-objective optimization of spectrum utilization or handoff rate, the co-optimization of these two necessary objectives in CR networks has not been achieved. In this paper, we propose a Two-tier Cooperative Spectrum Allocation method (TCSA) to solve these two problems. TCSA consists of two functional parts: one is a Spectrum Adjacency Ranking algorithm implemented at the secondary users' terminals to satisfy the QoS requirements for different wireless multimedia applications; and the other is a Max Hyper-weight Matching algorithm implemented at the cognitive engines of CR networks to co-optimize spectrum utilization and secondary users' spectrum handoff rate. Simulation results show that, compared with the other Random matching algorithm and Cost minimized algorithm, TCSA can significantly improve the performance of CR networks in terms of secondary users' throughput and spectrum handoff rate.
机译:无线多媒体应用的快速增长增加了对频谱资源的需求,但是当今的频谱资源变得越来越稀缺,并且所分配频谱的很大一部分效率低下。提出了认知无线电(CR)技术来解决当前频谱效率低下的问题,并依靠动态频谱分配为用户提供无处不在的无线接入环境。但是,在先前的工作中存在两个未解决的问题:1)基于简化的服务质量(QoS)统一假设,无法满足不同无线多媒体应用程序的特定要求; 2)针对频谱利用率或切换率的单目标优化,尚未实现CR网络中这两个必要目标的共同优化。在本文中,我们提出了一种两层合作频谱分配方法(TCSA)来解决这两个问题。 TCSA包含两个功能部分:一个是在辅助用户终端上实现的频谱邻接排名算法,以满足不同无线多媒体应用的QoS要求;另一个是在CR网络的认知引擎上实现的最大超权重匹配算法,以共同优化频谱利用率和次要用户的频谱切换率。仿真结果表明,与其他随机匹配算法和成本最小化算法相比,TCSA可以从次级用户的吞吐量和频谱切换率方面显着提高CR网络的性能。

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