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dc.contributor.author謝易霖en_US
dc.contributor.author蘇育德en_US
dc.date.accessioned2014-12-12T01:14:47Z-
dc.date.available2014-12-12T01:14:47Z-
dc.date.issued2007en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#GT009513503en_US
dc.identifier.urihttp://hdl.handle.net/11536/38345-
dc.description.abstract快速且準確的頻譜偵測對於建立可靠的感知無線網路(cognitive wireless networks) 中是很重要的。合作式的頻譜偵測可以減少偵測的時間並增加其可靠度與系統的靈活性。然而在合作式偵測中參與感測器(sensors)越多,傳送給決策中心(fusion center)時所需的控制通道(control channel)之頻寬越大。在這篇論文中,我們使用分散式(distributed)逐次(sequential)的頻譜偵測法去調整、降低控制通道所需的頻寬。此技術不僅減少了偵測的時間且表現得比固定取樣長度(fix sample size)的合作式偵測好。系統的效能通常以遺漏機率(miss probability)和誤警機率(false alarm probability)之大小來衡量。我們提出一套完整的設計方法與流程,可以利用調整各感測器的門檻值(threshold values)來達成系統所要求的效能以及控制通道的大小(即所需傳送的平均位元數)。zh_TW
dc.description.abstractFast and accurate spectrum sensing is crucial in realizing a reliable cognitive network. Cooperative spectrum sensing can help reducing the mean detection time and increasing the agility of the sensing process. However, when the number of cognitive users is large, the bandwidth need for the control channel that are used to report the secondary user nodes' results to the fusion center may become excessively large. In this paper, we apply the sequential probability ratio test (SPRT) to control the average number of the reporting bits. It is shown that the proposed technique not only reduces the mean detection time and bandwidth but also outperforms its non-sequential counterpart. We derive the relationships amongst the global performance, miss probability and false alarm probability and show how to control the average number of reports by thresholding the distributed cognitive users.en_US
dc.language.isoen_USen_US
dc.subject感知式網路zh_TW
dc.subject逐次檢測zh_TW
dc.subject分散式zh_TW
dc.subjectcognitive radioen_US
dc.subjectsequential probability ratio testen_US
dc.subjectdistributeden_US
dc.title用於感知無線電網路之分散式逐次頻譜感測zh_TW
dc.titleDistributed Sequential Spectrum Sensing for Cognitive Radio Networken_US
dc.typeThesisen_US
dc.contributor.department電信工程研究所zh_TW
Appears in Collections:Thesis


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