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A New Dynamic Spectrum Access Algorithm for TV White Space Cognitive Radio Networks

机译:一种新的电视白空间认知无线电网络动态频谱接入算法

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摘要

As more user applications emerge for wireless devices, the corresponding amount of traffic is rapidly expanding, with the corollary that ever-greater spectrum capacity is required. Service providers are experiencing deployment blockages due to insufficient bandwidth being available to accommodate such devices. TV White Space (TVWS) represents an opportunity to supplement existing licensed spectrum by exploiting unlicensed resources. TVWS spectrum has materialised from the unused TV channels in the switchover from analogue to digital platforms. The main obstacles to TVWS adoption are reliable detection of primary users (PU) i.e., TV operators and consumers, allied with specifically, the hidden node problem. This paper presents a new Generalised Enhanced Detection Algorithm (GEDA) that exploits the unique way Digital Terrestrial TV (DTT) channels are deployed in different geographical areas. GEDA effectively transforms an energy detector into a feature sensor to achieve significant improvements in detection probability of a DTT PU. Furthermore, by framing a novel margin strategy utilising a keep out contour, the hidden node issue is resolved and a viable secondary user sensing solution formulated. Experimental results for a cognitive radio TVWS model have formalised both the bandwidth and throughput gains secured by TVWS users with this new paradigm.
机译:随着用于无线设备的更多用户应用程序的出现,相应的业务量正在迅速扩大,这必然要求更大的频谱容量。由于没有足够的带宽来容纳此类设备,因此服务提供商正在遇到部署障碍。电视空白空间(TVWS)代表了通过利用未许可资源补充现有许可频谱的机会。从模拟到数字平台的转换,TVWS频谱已经从未使用的电视频道中实现。采用TVWS的主要障碍是可靠检测主要用户(PU),即电视运营商和消费者,尤其是隐藏节点问题。本文提出了一种新的广义增强检测算法(GEDA),该算法利用了在不同地理区域部署数字地面电视(DTT)频道的独特方式。 GEDA有效地将能量检测器转换为特征传感器,从而显着提高了DTT PU的检测概率。此外,通过利用保持轮廓构建新的边距策略,解决了隐藏节点问题,并制定了可行的辅助用户感知解决方案。认知无线电TVWS模型的实验结果已经正式化了TVWS用户使用此新范例确保的带宽和吞吐量增益。

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