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dc.contributor.author鄭仲傑en_US
dc.contributor.authorCheng, Chung-Chiehen_US
dc.contributor.author伍紹勳en_US
dc.contributor.authorWu,Sau-Hsuanen_US
dc.date.accessioned2014-12-12T01:55:52Z-
dc.date.available2014-12-12T01:55:52Z-
dc.date.issued2012en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#GT079913523en_US
dc.identifier.urihttp://hdl.handle.net/11536/49303-
dc.description.abstract隨著科技的進步,對於無線通訊的需求也跟著成長。 因此,對於行動無線數據網路有一些挑戰,例如:使用者人數的成長,高頻寬的需求,功率的消耗以及動態網路的負載。為了要解決這些問題,有些電信業者提出了雲端架構下的行動數據網路的概念,嘗試利用雲端的特性來解決目前遇到的問題。然而對於這些雲端架構系統的資料欠缺,因此我們以自己提出的CRCN的架構來作為分析的依據。在我們的系統架構下,透過中控式的資源分配以及在AP上對於使用者做排程,我們可以更有效率的使用頻譜。在這篇論文當中,我們主要是針對區域內的資源分配做探討。為了要在服務越多的使用者前提下使用最少的功率,因此我們分別提出了最佳解與次佳解的演算法。在案例研究中,我們以台北市為例子,嘗試去驗證CRCN可以服務台北市這樣大尺度的系統。 根據模擬結果與CRCN的架構,我們分別去評估說在不同的時間與地點,分別要布建多少AP和使用多少VM才可滿足需求。最後的結果顯示說透過雲端運算的特性以及CRCN的系統架構,我們的確是可以服務大尺度的系統。zh_TW
dc.description.abstractAs technology makes great progress, the demand for wireless communication grows up. Therefore, there are some challenges to mobile wireless data networks, such as the growth of mobile users, high bandwidth demand, power consumption and dynamic network loading. In order to resolve these problems, some operators propose the concept of cloud-based data network. Operators attempt to use the features of cloud to solve those problem. However, there is insufficient information about realistic statistics of cloud-based systems. Therefore, we do a feasibility study. Through centralized resource allocation and scheduling to access points(APs), the spectrum usage could be efficiently enhanced. In this thesis, we focus on the system study of resource allocation in such a cloud-based network. We proposed optimal and suboptimal schemes so that we could serve maximal users with the minimal power to meet each of their requirement. In the case study, we take Taipei city as an example, trying to verify that CRCN can support large scale systems. According to simulation result and architecture of CRCN, we assess the requirements of APs and virtual machines in different district and different time. The results show that the feature of cloud computing and the architecture of CRCN can support large scale systems.en_US
dc.language.isoen_USen_US
dc.subject感知無線電zh_TW
dc.subject功率控制zh_TW
dc.subject雲端計算zh_TW
dc.subjectCognitive Radioen_US
dc.subjectPower controlen_US
dc.subjectCloud computingen_US
dc.title以功率的觀點對於雲端架構下之感知無線電行動網路的可行性分析zh_TW
dc.titleFeasibility Assessment for A Cloud-Based Cognitive Radio Mobile Network- A Power Perspectiveen_US
dc.typeThesisen_US
dc.contributor.department電信工程研究所zh_TW
Appears in Collections:Thesis