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研究生: 彭彥鈞
Peng, Yen Chun
論文名稱: 多點協調網路系統下之非正交多頻分址技術之資源配置
Efficient Resource Allocation for Non-Orthogonal Multiple Access in Downlink Coordinated Multi-point Systems
指導教授: 高榮駿
Kao, Jung Chun
口試委員: 楊舜仁
Yang, Shun Ren
趙禧綠
Chao, Hsi Lu
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 資訊工程學系
Computer Science
論文出版年: 2015
畢業學年度: 103
語文別: 英文
論文頁數: 47
中文關鍵詞: 非證交多頻分址多點協調資源配置干擾消除
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  • 透過連續干擾消除(SIC)的方式,下行鏈路非正交多頻分址技術(NOMA)提高了系統效能和基地台(BSs)服務範圍邊緣的使用者設備(UEs)的效能。但是,在參考文獻中的非正交多頻分址技術對於使用者設備有位置和傳送功率這兩種限制。基地台以低傳送功率發送訊號給附近的使用者設備,而以高傳送功率給距離遠的使用者設備。我們提出了一個機率模型,再屏除這些限制後依然可以計算正確的系統效能。此外,NOMA的概念還可以結合多點協調技術(CoMP)。彼此合作的基地台發送訊號給鄰近自身的使用者設備和一個合作傳輸的基地台邊緣使用者設備,進而提升系統效能。為此技術我們也提出一個機率模型。基於上述系統效能計算的公式,我們提出資源配置的演算法,目標是最大化滿足QoS的使用者設備數量。模擬的結果說明我們在滿足QoS的使用者設備數量優於比較的演算法。


    The downlink non-orthogonal multiple access (NOMA) with successive interference cancellation (SIC) improves both the system throughput and cell edge user equipments (UEs) throughput. However, there are constraints on position and transmit power of UEs in NOMA. The base stations (BSs) transmit signals to the UE nearby and the UE far away with lower power and higher power, respectively. Without the constraint, we propose a probability model to derive the exactly throughput of UEs in NOMA. Moreover, the concept of the NOMA can combine with that of coordinated multipoint (CoMP). The associated BSs transmit signals to the UEs near themselves while also transmit signal to a cell-edge UE between two cells; with that it can improve the system throughput. We also propose a probability model for NOMA+CoMP. Based on the probability model, we propose an efficient resource allocation algorithm whose objective function is to maximize the number of satisfied UEs. The simulation results show that the proposed algorithm outperforms the compared algorithm in number of the satisfied UEs.

    Acknowledgements i Abstract ii 中文摘要 iii Table of Contents iv List of Figures vi Chapter 1. Introduction 1 1.1 Concept of CoMP 1 1.2 Non-Orthogonal Multiple Access (NOMA) 2 1.3 Successive Interference Cancellation (SIC) 3 Chapter 2. Related Work 6 Chapter 3. System Model 9 3.1 NOMA Scheme in Cells 10 3.2 Successful Decoding Probability in NOMA 11 3.3 NOMA in CoMP-Based Cellular Network 13 3.4 Successful Decoding Probability in NOMA+CoMP 14 3.5 Power Allocation 16 Chapter 4. Efficient Resource allocation Algorithm 17 Part I: NOMA and NOMA+CoMP (Given Efficiency Ranges from 1 to 2) 19 Part II: Borrow Resource from Neighboring Cell (Given Efficiency is 1) 24 Part III: Serving UE Based on OFDMA (Given Efficiency is 1) 26 Part IV: More than One RBs are Allocated to A UE Based on OFDMA (Given Efficiency is less than 1) 26 Chapter 5. Simulation 27 5.1 Compared Algorithm 27 5.1.1 Greedy NOMA Resource Allocation Algorithm 27 5.1.2 Optimal OFDMA Resource Allocation Algorithm 28 5.2 Simulation Settings 28 5.3 Simulation Results 29 Chapter 6. Conclusion 44 Bibliography 45

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