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研究生:楊璿
研究生(外文):Hsuan Yang
論文名稱:下行多使用者多輸入多輸出系統之低複雜度使用者配對策略
論文名稱(外文):Low Complexity User Pairing Strategies for Downlink Multi-User MIMO Systems
指導教授:邱茂清邱茂清引用關係沈文和
指導教授(外文):Mao-Ching ChiuWern-Ho Sheen
口試委員:邱茂清沈文和陳喬恩劉維正
口試委員(外文):Mao-Ching ChiuWern-Ho SheenChiao-En ChenWei-Cheng Liu
口試日期:2011/07/29
學位類別:碩士
校院名稱:國立中正大學
系所名稱:通訊工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2011
畢業學年度:99
語文別:英文
論文頁數:31
外文關鍵詞:downlinkmulti-user MIMO
相關次數:
  • 被引用被引用:0
  • 點閱點閱:232
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  • 下載下載:4
  • 收藏至我的研究室書目清單書目收藏:0
無線電頻譜是有限而珍貴的資源,因此多使用者多輸入多輸出無線網路之頻譜分配問題已經被熱烈討論,而挑選使用者配對也可以視為頻譜分配的一種。適當使用配對策略可以明顯改善系統吞吐量並增加頻譜利用率。我們提出兩個低複雜度使用者配對策略,和率配對搭配簡易預編碼策略的目標,是挑選兩位具最佳和率之使用者共享頻譜資源,以提升系統吞吐量並節省資源。然而不論預編碼矩陣的計算複雜度高低與否,此演算法需要事先計算所有配對組合的預編碼矩陣。為此我們提出特徵值配對策略,根據通道矩陣函數的特徵值挑選使用者,而不需考慮其預編碼矩陣為何。模擬結果顯示此演算法的效能相當接近前一個演算法而具有複雜度較低的優勢。我們同時也提出一個新線性預編碼演算法 - 梯度預編碼。它使用迭代的方式,持續計算和率對預編碼矩陣的梯度直到得到收斂解。梯度預編碼比其他線性預編碼矩陣具有更佳的效能,儘管複雜度也相對較高。
Since the radio spectrum is a finite and precious resource, the spectrum arrangement for multi-user MIMO (MU-MIMO) wireless networks is a well discussed problem. User pairing can be considered as a kind of spectrum arrangement. Employing the pairing schemes appropriately can improve the system throughput significantly and facilitate effective use of radio spectrum. In this paper, we propose two complexity user pairing strategies for MU-MIMO downlink scenario. The goal of sum rate pairing strategy is selecting two users which have the maximum sum of data rate in certain frequency resources to enhance system throughput. However, this pairing strategy needs to calculate the precoding matrices before pairing, regardless of the level of the complexity of calculating the precoding matrices. We propose a low-complexity eigenvalue pairing strategy based on eigenvalues of function of channel state information (CSI) without regard of precoding matrices. Simulation results show that the algorithm has significantly low complexity and provides performance that is very close to the sum rate pairing strategy.We propose a new linear precoding scheme, Gradient precoding. It iteratively takes the partial derivative of sum-rate with respect of precoding matrix until obtaining a convergent solution. It performs better than other linear precoding schemes, in spite of the higher complexity.

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4
2.1 Downlink MU-MIMO Systems . . . . . . . . . . . . . . . . . . . . . . . .4
2.2 Downlink 2-user MIMO Systems . . . . . . . . . . . . . . . . . . . . .5
3 Precoding Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
3.1 Zero forcing(ZF) precoding . . . . . . . . . . . . . . . . . . . . . . . . . .8
3.2 Joint leakage suppression (JLS) precoding . . . . . . . . . .10
3.3 Gradient precoding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11
4 Pairing Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
4.1 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14
4.2 User Pairing Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
4.2.1 Sum-Rate-Pairing with simpli ed precoding . . . . . . . . 15
4.2.2 Eigenvalue-Pairing Algorithm . . . . . . . . . . . . . . . . . . . . .16
5 Numerical Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21
6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
7 Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
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