基于认知无线电无线网状网络的高效视频点播系统

Mohammad Siraj, Z. Abbasi
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引用次数: 3

摘要

认知无线电(Cognitive Radio, CR)是一种新兴的、有发展前景的技术,它通过利用许可频谱的空白空间,有效地利用频谱,解决频谱短缺的问题。视频点播(VoD)是当今非常流行的服务。众所周知,视频点播服务需要大量的带宽。预计CR WMNs将为视频流提供急需的带宽,因为CR WMNs能够访问大部分未充分利用的许可频谱。在认知无线mesh网络中,干扰是影响认知无线mesh网络性能的关键问题。随着用户数量的增加,干扰也会增加,从而导致低吞吐量。本文首先提出了CR WMNs的解析模型。我们还提出了一种高效的视频点播模型和优化方法,以最大限度地减少干扰,为视频点播服务提供急需的更高网络容量。仿真结果表明,当并发视频点播会话数增加时,我们提出的方法是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Efficient Video on Demand System over Cognitive Radio Wireless Mesh Networks
Cognitive Radio (CR) is an emerging and promising technology which is predicted to solve the problem of spectrum shortage by utilization of the spectrum efficiently by exploiting the licensed spectrum white spaces. Video on demand (VoD) is a very popular present day service. It is a well-known fact, that video on demand internet service needs a large amount of bandwidth. CR WMNs is envisaged to provide the much needed bandwidth for video streaming as CR WMNs has the ability to access a large part of the under-utilized licensed spectrum. In CR WMNs interference is a critical issue which degrades cognitive radio wireless mesh networks (CR WMNs) performance. As the number of users rises, interference also increases resulting in low throughput. In this paper first an analytical model for CR WMNs has been presented. We have also presented an efficient VoD model and an optimizing approach which minimizes interference to provide a much needed higher network capacity to VoD services. Simulation results show effectiveness of our proposed approach as there is an increase in the number of concurrent VoD sessions.
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