臺灣博碩士論文加值系統

隨著下世代行動通訊技術的發展，異質網路因為可以滿足用戶所
需要的高速度行動網路服務而受到關注，然而，雖然密集的小基地台
可以達到高流量，卻也讓干擾不斷提升，用戶也因為密集的小基地台
而過度換手。因此，如何減少干擾以及減少不必要的換手在未來的
5G 技術下變得很重要。本篇論文中將針對移動的使用者來探討資源
分配和換基地台的問題，藉以提升高密度網路下的系統效能。其中，
我們考慮如何適當地選取服務使用者的基地台以減少不必要的換基地
台問題，並且我們會保證每個使用者都會有一定的服務品質。本研究
將藉由選擇基地台和調整基地台傳輸功率的分配，進而設計一個使總
傳輸率達到最大的最佳化問題。但因為此問題為非凸優化問題，因此
我們需要透過一些數學轉換來讓本來的問題變成凸優化問題，之後透
過本研究所提出之以有速度的使用者為中心感測的資源分配機制，來
解決此問題。另外，我們的情境在某些狀況下可以接近另外兩個同樣
也是以使用者為中心的服務基地台選取方式：以距離為主的合作和以
數量為主的合作，因此我們可以透過分析這兩個選取方式來得到換手
率的封閉型式。模擬將驗證在使用者保證不同服務品質的需求和使用
者不同的速度下，本研究所提出的方法之效能，也會比較我們的方法
和以距離為主的合作和以數量為主的合作之效能。

In this paper, a joint interference management and handover problem for mobility user is investigated to enhance the system performance of cellular networks. Specifically, the transmission set selected of user equipments (UEs) are considered for reducing unnecessary handover. A quality-of service (QoS)-constrained problem is then designed to maximize mobility-aware sum rate through the joint strategies of power allocation and transmission set selection. However, the original optimization problem is a non-convex problem, so we need some mathematical transformation to transform original
problem to a convex problem. In order to solve the joint power allocation and transmission set selection problem, a user-centric mobility-aware resource allocation (UMRA) algorithm is proposed to tackle this problem. We also find two special cases from our scenario, namely distance-based cooperation (DBC) and number-based cooperation (NBC). And we can analyze these two scenario to derive the handover rate in closed-form. The simulation results show the utility which involves sum rate and handover cost of our proposed UMRA algorithm with different QoS requirements and velocity. And
compare our proposed UMRA algorithm with DBC and NBC scheme.

Chinese Abstract i
English Abstract ii
Contents iii
List of Figures v
List of Tables vi
1 Introduction 1
2 System Model and Problem Formulation 6
2.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.2 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . 10
3 Proposed User-centric Mobility-aware Resource Allocation
(UMRA) Algorithm 11
3.1 Problem Transformation . . . . . . . . . . . . . . . . . . . . . 11
3.2 Proposed UMRA algorithm . . . . . . . . . . . . . . . . . . . 15
4 Handover Rate Analysis 18
4.1 Number-based Cooperation . . . . . . . . . . . . . . . . . . . 20
4.2 Distance-based Cooperation . . . . . . . . . . . . . . . . . . . 22
4.3 Disjoint Clustering . . . . . . . . . . . . . . . . . . . . . . . . 23
5 Performance Evaluation 24
6 Conclusion 33
Bibliography 34

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