毫微微細胞覆蓋式正交分頻多工網路之分散式資源分配

Abstract

毫微微蜂巢式網路(femtocell)具有延伸網路涵蓋範圍、提昇網路傳輸容量、增加服務品質等優勢，此外也可以補強大型基地台（macrocell）無法涵蓋的區域和死角，並減輕其頻寬負荷。即使毫微微蜂巢式網路有上述好處，為了保持大型網路使用者的傳輸品質，這些毫微微蜂巢式網路皆會有最大功率下載限制。

在此篇文章中使用閉路存取之正交分頻多工存取(OFDMA)蜂巢網路，並深入探討如何提升通道傳輸容量以及干擾控制。我們使用中斷機制來量測大型網路使用者的訊號品質，除此之外我們也採用有干擾限制下之分散式迭代法來處理資源分配。中斷機率的運算可以讓毫微微蜂巢式網路基地台不需要知道大型網路使用者的確切位置、通道上的訊號以及受到的干擾。但每個毫微微蜂巢式網路基地台使用分散式方法計算通道傳輸容量時，則需要知其覆蓋範圍底下使用者通道狀況或是訊號干擾雜訊比。

毫微微蜂巢式網路基地台在分散式資源分配演算法裡的每一回合，會根據網路內使用者在頻帶上的通道狀態以及訊號干擾雜訊比，將頻帶適當的分配給其下之使用者，再使用注水演算法來分配所有頻帶上的功率。透過平均中斷機率的要求，每個頻帶上皆會有最大的功率限制。我們因此提出修正式注水演算法程序來最大化每個毫微微蜂巢式網路傳輸容量。當我們觀察到所提出的方法不一定都會收斂，因此我們再提出多個修正措施來增加收斂的機率。分散式資源分配也可以視為某種非合作式賽局，透過已知奈許平衡點之充分條件，試著將其與我們所提出的演算法和修正措施之收斂性做一個結合。

The deployment of femtocells is an attractive solution to cope with the capacity and coverage limitation of the existing macrocellular networks. For femtocells to overlay an existing macrocellular network, it is important that the signal qualities of macrocell users (mMSs) be maintained, i.e., the femto-users induced interference be limited to a tolerable level.

In this thesis, we discuss the capacity enhancement and interference control issues in a closed access two-tier orthogonal frequency division multiple access (OFDMA) based cellular network. We use the average outage probability as the measure of mMS signal quality and employ an iterative distributed resource allocation (RA) based interference control approach. The former measure avoids the need for a femto base station (fBS) to know the exact locations of mMSs and the related signal and interference link gains while the distributed approach assumes that each fBS has access to the link gains or signal to noise-plus-interference ratio (SINR) associated with all downlinks within its coverage only.

At each iteration of the distributed RA algorithm, each fBS selects a femto mobile station (fMS) for every subcarrier according to the link gain and SINR and uses a water-filling procedure for power allocation. The average outage probability requirement, however, impose a peak power constraint on each subcarrier. We thus suggest a modified water-filling procedure to maximize the sum capacity of a femtocell. As we observe that the proposed method does not necessarily converge, we propose several remedies to improve the convergence probability. Regarding the distributed RA as a noncooperative game and use a known sufficient condition for the existence of a Nash equilibrium point, we try to interpret the convergence behavior of our algorithm and its remedies.