臺灣博碩士論文加值系統

當毫微微型基地台(Femto base station)被重疊部屬於巨型基地台(Macro base station)的區域時，因為毫微微型基地台可以重複使用巨型基地台的頻段，以及部屬在巨型基地台信號被遮蔽之處，所以毫微微型基地台可有效改善重疊網路的整體吞吐量以及增加巨型基地台的覆蓋度。但是管理重複使用相同資源所造成的同階層干擾(co-tier interference)及跨階層干擾(cross-tier interference)，就成為一個重要的問題了!
本篇論文所提出的方法為基於圖論(Graph theory) 的一種中央化的(centralized)演算法，所建構出的加權干擾圖 (weighted interference graph)中，頂點為各個毫微微型基地台，彼此連線的權重則是兩基地台間的干擾。首先先把頻段分為兩種，第一種為尚無任何巨型基地台使用裝置(MUEs)使用的頻段，第二種則為已被巨型基地台使用裝置使用的頻段。而本篇論文將分為三段來討論此問題，第一段主要討論第一種頻段，將使用分群的方法將同階層干擾較嚴重的毫微微型基地台分開成不同群，如此同一群的基地台就可以重複使用相同資源。第二段則主要探討當使用共享式頻譜(shared spectrum)，毫微微型基地台要如何分配資源，以減輕同階層干擾及跨階層干擾的問題。而最後第三段的問題則主要著重於當巨型基地台使用裝置(MUEs)的數量有所增減時，如何根據前兩段的結果，提出根據使用者變化模式改變的簡單重新分配方法。

In femtocell and macrocell underlaying network, thank to spetrum reusage of Marcro base station, femto base stations can increase throughput and coverage of the cellular network effectively. However, cross-tier interference and co-tier interference come with the spectrum reusage and remain as a serious challenge to be dealt with.
In this thesis, we propose a centralized algorithm based on the graph theory. The algorithm constructs a weighted interference graph based on interference amount among femto base station, and the number of served users by each femto base station. The available spectrums for femto base stations are divided into two categories: Macro User Equipments (MUEs)-free subchannels and MUEs-occupied subchannels. In the first part of the thesis, we will discuss how to allocate the MUEs-free subchannels. According to the weighted interference graph, femtocells are grouped in order to minimize the co-tier interference by the proposed clustering algorithm. In the second part, we dicuss how to reuse MUEs-occupied subchannels and minimize co-tier and cross-tier interference at the same time by extending the clustering algorithm proposed in chapter 2. Finally, a dynamic resource sharing scheme is amended considering MUEs'' mobility. A markovian state machine is introduced to model the entering and leaving behaviors of MUEs. Consequently, this state machine is merged into the proposed clustering scheme and a dynamic clustering algorithm is achieved.

口試委員會審定書 #
誌謝 i
中文摘要 ii
ABSTRACT iii
CONTENTS iv
LIST OF FIGURES viii
LIST OF TABLES x
Chapter 1 引言與動機 1
1.1 起源 1
1.2 毫微微型基地台之優點 4
1.3 技術面之挑戰 5
1.3.1 頻譜問題 5
1.3.2 基礎建設問題 8
1.4 資源分配方法 8
1.4.1 獨立式頻段 8
1.4.2 共享式頻段 9
1.4.3 部分共享式頻段 9
1.5 存取模式 10
1.5.1 封閉存取 10
1.5.2 公開存取 11
1.5.3 混合式存取 12
1.6 論文動機 12
1.7 論文架構 13
Chapter 2 無巨型基地台使用者裝置網路之資源分配 15
2.1 章節簡介 15
2.2 系統模型 16
2.2.1 環境介紹 16
2.2.2 路徑衰減模型 17
2.3 現有文獻方法回顧 18
2.3.1 製作相鄰矩陣(adjacency matrix) 18
2.3.2 分群演算法 19
2.4 權重干擾圖分群演算法 20
2.4.1 建立權重干擾圖 20
2.4.2 計算邊的權重 21
2.4.3 權重干擾圖分群演算法(Weighterd Interference Graph Clustering Algorithm, WIGCA) 21
2.5 模擬結果 24
2.5.1 分群結果 24
2.5.2 效能分析 25
2.6 章節結論 30
Chapter 3 含有巨型基地台使用者裝置之資源分配 31
3.1 章節簡介 31
3.2 系統模型 32
3.2.1 環境介紹 32
3.2.2 路徑衰減模型 33
3.3 現有文獻回顧 35
3.4 資源分配方法 37
3.4.1 分配流程圖 37
3.4.2 建立干擾圖 38
3.4.3 干擾圖重複使用演算法(IGRA) 38
3.5 模擬結果 41
3.6 章節結論 44
Chapter 4 巨型基地台使用者個數變化之資源分配 46
4.1 章節簡介 46
4.2 系統模型 47
4.2.1 環境介紹 47
4.3 動態資源分配方法 48
4.3.1 分配流程圖 48
4.3.2 巨型基地台使用者個數狀態機 49
4.3.3 無巨型使用者裝置進入或離開 50
4.3.4 單一巨型使用者裝置進入 50
4.3.5 單一巨型使用者裝置離開 51
4.3.6 同時有一個巨型使用者裝置進入和離開 53
4.4 模擬結果 54
4.4.1 使用者裝置效能對毫微微型基地台個數之分析 54
4.4.2 穩態分析 59
4.5 章節結論 62
Chapter 5 總結及未來展望 63
5.1.1 總結 63
5.1.2 未來展望 64
Chapter 6 參考文獻 65

[1]F. J. Mullany, L. T. W. Ho, L. G Samuel, and H. Claussen, “Self-deployment,self-configuration: Critical future paradigms for wireless access networks,” in Lecture Notes on Computer Science LNCS, vol. 3457, pp. 58–68.
[2]S. Sharma, A. R. Nix, and S. Olafsson, Situation-aware wireless networks, IEEE
Communications Magazine, vol. 41, No. 7, pp. 44–50, 2003.
[3]A. G. Spilling, A. R. Nix, M. . Beach, n T. J. Harrold ,” Self-organisation in
future mobile communication ,” Electronics &; Communication Engineering
Journal, vol. 12, No. 3, pp. 133–147, 2000.
[4]H. Claussen, “ Autonomous self-deployment of wireless access networks in an
airport environment,” in Lecture Notes on Computer Science LNCS, vol. 3854,pp.
86–98. Springer, 2006.
[5]H. Claussen, “Distributed algorithms for robust self-deployment and self-configuration in autonomous wireless access networks,” in Proc. IEEE International Conference on Communications, vol. 4, pp. 1927–1932, June 2006.
[6]H. Claussen, L. T. W. Ho, H. R. K imi, F. J. M ll ny, n L. G. Samuel, I, “base
station: cognisant robots and future wireless access networks,” in Proc. 3rd IEEE
Consumer Communications and Networking Conference, Vol. 1, pp. 595–599,
January 2006.
[7]J. G. Andrew , “Interference Cancellation for Cellular System : A Contemporary Overview,” IEEE Wireless Commun., vol. 12, no. 2, pp. 19–29, 2005.
[8]A. M. Kuzminskiy and Y. I. Abramovich, “Second -Order Asynchronous
Interference Cancellation: Regularized Semi-Blind Technique and Non-Asymptotic Maximum Likelihoo Benchmark,” Signal Processing, vol. 86, no. 12, 3849–3863, 2006.
[9]3rd Generation Partnership Project , “High Speed Downlink Packet Access :
Physical Layer Aspects ,” 3GPP TR 25.858, 2002, http://www.3gpp.org/
ftp/Specs/html-info/25858.htm
[10]http://www.femtoforum.org/femto/
[11]A. Saleh, A. Rustako, and R. Roman, “Distributed antennas foe Indoor Radio
Communication ,” IEEE Trans. Commun., vol. 35, no. 12, pp. 1245–51, Dec.
1987
[12]C.-L. I, L. J. Greenstein,a nd R. D. Gitlin, “ Microell/ Macrocell Cellular
Architecture for Low- and High- Mobility Wireless Users,” IEEE JSAC, vol. 11,
no. 6, pp. 885–91, Aug. 1993.
[13]Presentations by ABI Research, Picochip, Airvana, IP.access, Gartner, Telefonica Espana, 2nd Int’l. Conf. Home Access Points and Femtocells; http://www.avrenevents.com/dallasfemto2007/purchase_presentations.htm
[14]W. Chadrasekhar, J. F.Andrew, and Al Gatherer, “Femtocell Network: A Survey,” IEEE Communications Magazine, pp. 59-67, Sept. 2008.
[15]Claussen, H. and Hobby J. D., “Deployment Options for Femtocells and Their
Impact on Existing Macrocellular Networks,” Bell Labs. Tech. J., vol. 13, no. 4, pp.145–160, 2009.
[16]S. Sahni and T. Gonzalez, “P-Complete Approximation Problems”, Journal of the ACM, Vol. 23, Issue 3, pp. 555-565, 1976.
[17]H. Li, X. Xu, D. Hu, X. Tao, P. Zhang, S. Ci, and H. Tang, “Clustering strategy based on graph method and power control for frequency resource management in femtocell and macrocell overlaid system,” J. Commun. and Networks, vol. 13, no. 6, pp. 664–677, Dec. 2011.
[18]3GPP TR36.921, “Home eNode B (HeNB) Radio Frequency (RF) requirements analysis (Release 9),” v9.0.0, Mar. 2010
[19]X. Chu, Y. Wu, L. Benmesbah, and B. Ling, “Resource allocation in Hybrid macro/femto networks,” in Proc. IEEE WCNCW, Sydney, Australia, Apr. 2010.