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dc.contributor.author楚偉生en_US
dc.contributor.authorChuu, Wei-Shengen_US
dc.contributor.author桑梓賢en_US
dc.contributor.authorSang,Tzu-Hsienen_US
dc.date.accessioned2014-12-12T02:44:45Z-
dc.date.available2014-12-12T02:44:45Z-
dc.date.issued2014en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#GT070150277en_US
dc.identifier.urihttp://hdl.handle.net/11536/76084-
dc.description.abstract在第四代無線通訊網路的普及下,使用者的人數日與劇增,干擾的影響也越來越不可忽視。為了降低干擾對通訊系統的影響,許多人提出干擾抑制(Interference Mitigation)的方案,主要可以在實體層(Physical layer)以訊號處理方式解決,或是在媒體存取控制層(Media Access Control layer)用資源分配的方式解決。 而實體層中,干擾對齊(Interference alignment)是近幾年崛起的干擾抑制方案,通過選擇部分發射端來合作,同時設計傳輸的編碼器和解碼器,在接收端接收訊號時能將來自其他發射端的干擾對齊至同一個子空間,而訊號就能在一個無干擾的子空間中傳輸,廣義來說,這也是一種波束成型(Beamforming)的方法。 這個技術在理論中已被證實能在高訊雜比(Signal to Noise Ratio)時達到最大的自由度(Degree of freedom)[3],也就是這個干擾通道的最大通道容量。雖然消除干擾的效能十分顯著,但也存在著兩個大問題,一是每個傳送端都需要知道需要被消除的干擾源的通道狀況資訊(Channel State Information),對骨幹網路來說是個大的挑戰,二是合作人數上的限制,直觀來說,有限的天線數只能消除有限的干擾源,因此存在了另一個問題就是我們如何決定該消除系統中的那些干擾。  目前可行的解決方案中,是先將系統中的所有發射端藉由叢集演算法分類,每個叢集內部再分別使用干擾對齊,既可以符合干擾對齊可行性上的限制,也可以減輕大量的通道資訊對骨幹網路的負擔。 而這篇論文主要著眼點在於叢集內部的能量分配,藉由兩段式的干擾抑制方案,第一階段先以叢集演算法找出干擾較強的區域形成叢集,將資源拿去消除較強的干擾,第二階段則是再針對叢集內部干擾較強的地方預先減少配置的能量以減低干擾,這一個跨層的干擾管理方案能夠減少多用戶干擾網路的干擾。zh_TW
dc.description.abstractNowadays, 4G wireless communication network get much popular, the number of users increase quickly so that the impact of interference cannot be ignored. In order to reduce the impact of interference in communication systems, many people proposed interference suppression schemes. It is mainly solved by signal processing in the physical layer or by resources allocation in the media access control layer (MAC layer). In the physical layer, interference alignment (IA) is a promising solution of interference suppression scheme in recent years. By choosing the parts of transmitters to cooperate, and designing encoders and decoders. The received signals from other transmitters are aligned to the same sub-space at the receiver, and desire signal can transmit in interference-free signal subspace. Generally speaking, it’s a beamforming technique. This technique has been proven to reach the maximum degree of freedom (DoF) at high SNR (Signal to Noise Ratio) in theory, which is the maximum capacity of this interference channel. Although the performance of IA is significant, but there are two existing problems. One is every transmitters needs to know the channel status information (CSI) of each interference channels, it’s a big challenge to backhaul networks. The other is limitation of the number of cooperative transmitters. The limited number of antennas can only eliminate limited interference, so there is another problem is how we decided which interference should be eliminated. In current feasible solution is dividing all transmitters into many isolated groups by clustering algorithm, and applying interference alignment in each cluster. This method not only satisfy the feasibility constraints of interference alignment, but also reduce the large number of channel information in the backhaul network loading. The main idea of this paper is focus on power allocation intra cluster by utilizing a two-stage interference suppression scheme. The first stage is searching the region which with stronger interference to form a cluster with K-means clustering algorithm, and eliminate interference. The second stage is power pre-configured intra cluster to reduce interference stronger place to minimize interference. This cross layer interference management scheme jointly reduces the interference of multiuser interference network.en_US
dc.language.isozh_TWen_US
dc.subject干擾對齊zh_TW
dc.subject叢集化zh_TW
dc.subjectinterference alignmenten_US
dc.subjectclusteringen_US
dc.title使用功率分配的叢集式干擾對齊zh_TW
dc.titleA Method of Clustered Interference Alignment with Power Allocationen_US
dc.typeThesisen_US
dc.contributor.department電子工程學系 電子研究所zh_TW
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