臺灣博碩士論文加值系統

在此篇論文中我們考慮一個合作式多基地台(BS)系統以及在其基地台之間獨立的載波頻率偏移(CFOs)和由高速可預測及低速不可預測用戶設備(UEs)所導致的都卜勒頻率偏移(DFOs)。載波頻率偏移效應所堆積的相位錯誤會惡化合作式系統的頻譜效率以及總系統速率。除此之外，都卜勒頻率偏移在高速移動的情況中像是高速鐵路(HSR)下是不可被忽略的。由於高速移動用戶設備的可預測性，這給予我們基於固定軌跡及準確時刻表的動機來建構出預測式資料庫，希望藉此來預補償都卜勒頻率偏移。我們擬議在多基地台端做估測以及校正不只是由用戶設備所引起的都卜勒頻率偏移以及基地台端所引起的載波頻率偏移。我們的方法始於基地台端的估測(UE Initiated)或是用戶設備端的估測(BS Initiated)來估計基地台的載波頻率偏移，其數值之後會被送至基地台端。由於用戶設備的高度可預測性，我們利用在基地台端的預測式資料庫來補償用戶設備所引起的都卜勒頻率偏移，以及當預測不準確時修正其資料庫。在研究結果中展示了我們所提倡的預測修正的迭代法會在數次迭代中收斂，以及提倡的頻率同步技術會得到好的系統表現。

We consider a coordinated multiple base station (BS) system and the associated problem of independent carrier frequency offsets (CFOs) at BSs as well as Doppler frequency offsets (DFOs) induced by both predictable high mobility and unpredictable low mobility user equipments (UEs). The effect of CFO causes accumulated phase errors which degrades the spectral efficiency and sum-rate of coordinated system. Besides, DFO is no longer negligible in high mobility condition such as high speed rail (HSR). Because of the highly predictable characteristic of high mobility UE, this motivates us to construct a prediction database based on fixed path and accurate time schedule for DFO pre-compensation. Our proposal is estimation and correction of both UE-induced DFO and BS-side CFO at the BSs. The method starts with formation of BS-side estimate (UE Initiated) or UE-side estimate (BS Initiated) of the BS CFOs, which is later fed back to BSs. Due to the fact that UE is highly predictable, we compensate the UE-induced DFO by prediction database at BSs and refine the database when our prediction is inaccurate. It is demonstrated that our proposed prediction refinement algorithm will converge within few iteration, and proposed frequency synchronization techniques achieves in good system performance.

1 Introduction 1
1.1 Coordinated Multi-point Transmission and Reception . . . . . 1
1.2 High-Speed Rail . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Carrier Frequency O set and Doppler Frequency O set . . . . 5
1.4 State-of-the-art . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.5 Motivation and Proposed Predictive Method . . . . . . . . . . 8
1.6 Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2 System Model and Problem Formulation 11
2.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.2 Preliminary . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.3 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . 18
2.3.1 Case 1: UE-induced DFO . . . . . . . . . . . . . . . . 18
2.3.2 Case 2: BS-side CFO . . . . . . . . . . . . . . . . . . . 20
2.3.3 Case 3: UE-induced DFO and BS-side CFO . . . . . . 22
3 Analysis of Case 1: UE-induced DFO 23
3.1 DFO in HSR . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.2 Prediction Database . . . . . . . . . . . . . . . . . . . . . . . 25
3.3 Predictive DFO Compensation . . . . . . . . . . . . . . . . . . 28
4 Analysis of Case 2: BS-side CFO 32
4.1 Multiple CFO Estimation . . . . . . . . . . . . . . . . . . . . 32
4.2 Cram er-Rao Lower Bound . . . . . . . . . . . . . . . . . . . . 36
5 Analysis of Case 3: UE-induced DFO and BS-side CFO 38
5.1 Preliminary . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
5.2 UE Initiated Frequency Synchronization . . . . . . . . . . . . 41
5.3 BS Initiated Frequency Synchronization . . . . . . . . . . . . . 45
5.4 Decision Criterion . . . . . . . . . . . . . . . . . . . . . . . . . 48
5.5 DFO Prediction Re nement . . . . . . . . . . . . . . . . . . . 49
5.6 Design of Stepsize and Threshold in DFO Prediction Re nement 55
6 Simulation Result 57
6.1 Environment Description . . . . . . . . . . . . . . . . . . . . . 57
6.2 Case 1: UE-induced DFO . . . . . . . . . . . . . . . . . . . . 61
6.2.1 Case 1 Simulation Result: DFO versus Normalized Distance
. . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
6.2.2 Case 1 Simulation Result: Sum-rate versus Time . . . 66
6.2.3 Case 1 Simulation Result: Sum-rate versus Normalized
Distance . . . . . . . . . . . . . . . . . . . . . . . . . . 68
6.2.4 Case 1 Simulation Result: Sum-rate versus Number of
UE and BS . . . . . . . . . . . . . . . . . . . . . . . . 70
6.3 Case 2: BS-side CFO . . . . . . . . . . . . . . . . . . . . . . . 72
6.3.1 Case 2 Simulation Result: Sum-rate versus Number of
UE and BS . . . . . . . . . . . . . . . . . . . . . . . . 72
6.4 Case 3: UE-induced DFO and BS-side CFO . . . . . . . . . . 74
6.4.1 Case 3 Simulation Result: Residual DFO versus Iteration
Times . . . . . . . . . . . . . . . . . . . . . . . . . 74
6.4.2 Case 3 Simulation Result: Sum-rate versus Number of
UE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
6.4.3 Case 3 Simulation Result: Sum-rate versus Number of
BS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
7 Conclusion 81
8 Future Work 83
Bibliography 84

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