自我組織毫微蜂巢式基地台基於干擾之分群

Abstract

為了達到更高的傳輸速率及無痕的網路連接，超微型蜂巢式基地台(femtocells)被認為是固定式與移動式技術整合的關鍵。超微型蜂巢式基地台由使用者安裝，必須具備自我組織管理的能力，可以自動化將不同的基地台結合在一起，特別是在城市裡密集部署的地方，以避免使用相同通道造成的干擾。為因應上述問題，在本篇論文中將提出一個兩階段性超微型蜂巢式基地台協力的演算法。首先在分群方面，根據基地台或是使用者對干擾的量測，有兩種方法將其彼此分組。其次，根據群組的分布，設計出頻帶分配機制。在整個研究過程中，如何依據干擾來分群是最關鍵的部分，因此，多種參數例如，功率設置的門檻或是每個群組中基地台個數的限制等，都需要經過縝密的思考及計算。在模擬中，將比較兩種不同分群方式及其對應參數帶來的效能，結果顯示出超微型蜂巢式基地台使用者的SINR與中斷概率會有大幅顯著的進步，而代價只需犧牲一點點的系統容量。

To achieve the goal of higher transmission rate and seamless internet access everywhere, femtocells are foreseen to be a key fixed-mobile convergence technology. As femtocells will be user-installed, self-organization techniques are required to automatically integrate themselves into the network and avoid co-femtocell interference, especially in urban dense deployment area. To cope with these challenges, a two-step femtocell-cooperation algorithm has been designed in this thesis. The first step is the clustering phase, during which femtocells will form groups with other femtocells according either to femtocell Base Station or to femtocell user interference measurements, thus setting two types of methods. Then, a frequency allocation scheme is proposed based on the grouping distribution; it corresponds to the tuning phase. The interference based clustering is the key part of this work; it has therefore been studied and evaluated according to several sets of parameters like power threshold or limit member per cluster. The results compare the performance of the two clustering methods with their parameters and show that the femtocell user SINR and the outage probability can be highly improved but at a capacity cost.