IEEE 802.16e是目前無線都會網路的媒介存取控制的國際標準（也就是俗稱的WiMAX）。為了進一步提昇網路的傳輸量及擴展基地台的涵蓋範圍，IEEE又於2009年制訂了802.16j的國際標準。隨著智慧型手機的普及，許多無線都會網路皆有提供多播服務。另一方面，由於行動台大多是使用電池作為電力來源，因此省電機制也就變得很當重要。本論文探討802.16j無線中繼網路中的省電多播排程問題，目標是使得網路的multicast energy efficiency最大。我們首先證明此一問題為NP-complete。接著我們修改SMBC-AMC的方法，使其適用於802.16j的環境。此一方法稱為SMBC-relay。由於SMBC-relay可能造成資料的重複傳送，因此我們提出另一個解決方案，稱之為GAMS。在GAMS裡頭，每筆multicast data只會被傳送一次；此外，GAMS採用基因演算法來求得此一問題的近似最佳解。採用基因演法的一個重大考量是基地台可以在任意時間終止演算法的執行。模擬實驗結果顯示，即使我們限制GAMS的執行時間不得超過一個multicast superframe，GAMS所所產生的多播排程解，其multicast energy efficiency仍然勝過SMBC-relay。

IEEE 802.16e （also known as Mobile WiMAX） is currently the international MAC （medium access control） standard for wireless metropolitan area networks. To enhance the network throughput and extend the coverage of base station, IEEE then defined the 802.16j standard. Clearly, one of the popular applications for WiMAX is the multicast service. On the other hand, the design of power saving technologies is important since mobile stations are often powered by batteries. In this thesis, we study the maximum energy-efficient multicast scheduling （MEMS） problem for an IEEE 802.16j network with transparent mode. Specifically, the base station should determine how to schedule the multicast data in a multicast superframe such that the multicast energy efficiency of network is maximal. We first prove that the MEMS problem is NP-complete. Then on the basis of SMBC-AMC, we propose its variant, called SMBC-relay, to solve this problem. However, in SMBC-relay, the base station may send the same multicast data several times, wasting the scarce bandwidth. Hence we we propose a genetic algorithm-based multicast scheduling algorithm, called GAMS. One of the key features of GAMS is that the base station can control when to terminate the algorithm by stopping the evolution at any time. Simulation results show that GAMS significantly outperforms SMBC-relay in terms of multicast energy efficiency.

論文審定書 i
致謝 ii
摘要 iii
Abstract iv
目錄 v
圖次 vii
表次 x
第一章 序論 1
1.1動機 2
1.1.1 Relay對於multicast的影響 2
1.1.2 Multicast scheduling對於省電的影響 2
1.2 貢獻 5
第二章 相關文獻 7
第三章 背景知識 10
3.1 訊框架構 10
3.2 正交分頻多重存取 10
3.3 Multicast Superframe 11
3.4調變及SNR計算 12
第四章 省電多播排程 13
4.1 問題定義 13
4.2 NP-Complete証明 15
4.3 SMBC-relay 19
4.4 以基因演算法為基礎的省電多播排程 27
4.4.1 基因演算法的架構 27
4.4.2 染色體定義 28
4.4.3 計算適應函數值 29
4.4.4演化程序 29
第五章 模擬實驗 32
5.1 模擬環境及參數 32
5.2 迭代次數的影響 33
5.3 GAMS的程式執行時間 34
5.4資料需求機率對energy efficiency的影響 36
5.5 Mobile Stations個數對Energy Efficiency的影響 38
5.6 Subchannels個數對Energy Efficiency的影響 40
5.7 Relays個數對Energy Efficiency的影響 40
5.8 Mobile Stations地理位置分佈的影響 41
5.9 資料需求機率分佈對傳輸排程的影響 44
5.10 資料熱門程度對Energy Efficiency的影響 46
第六章 結論 50

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