臺灣博碩士論文加值系統

在未來正交分頻多工(Orthogonal Frequency Division Multiplexing)行動網路中，基地台將會採用多輸入多輸出(Multi-input Multi-output)天線技術來改善對使用者的傳輸容量(Throughput)和鏈結可靠度(Link Reliability)。當基地台使用天線之空間多工技術，在下行連結的情況下，鄰近目前服務基地台的使用者的傳輸容量會被大量的增加，但是基地台全部的傳輸功率被分散到各個傳送天線，訊號干擾加雜訊比率(Signal to Interference-and-Noise Ratio)會隨著傳送天線個數增加而一直降低，特別是在細胞邊界的地方，會造成傳輸容量會嚴重下降，導致細胞服務範圍的縮減，為了涵蓋原先的服務範圍，電信業者需要佈建更多的基地台，這樣會增加業者基地台佈建的成本和增加使用者切換到不同基地台的次數。在實際的環境中，由於天線之間沒有足夠的距離和缺乏通道的散射效應(Scatter Effect)，天線相關性會存在於基地台或使用者，若傳送天線端存在天線相關性，多輸入多輸出天線之空間多工效能會大大的受到影響，如此，要解決多輸入多輸出天線之空間多工的涵蓋問題會變成一個更困難的工作。
我們在論文中提出兩種宏觀天線分集結合機制，增加使用多輸入多輸出天線之空間多工正交分頻多工行動網路基地台邊界的傳輸容量和進一步改善進行換手(Handover)的傳輸容量，一個是空頻編碼宏觀分集結合空間多工機制(Space-Frequency Block Code Macro-Diversity Combining Spatial Multiplexing)，另一個是循環延遲宏觀分集結合空間多工機制(Cyclic Delay Macro-Diversity Combining Spatial Multiplexing)，在相鄰的基地台之間增加傳送分集並結合基地台本身使用的天線之空間多工技術，在不增加傳送天線或基地台的個數下，我們可以同時得到多輸入多輸出之空間多工和空間分集的優勢，當使用者往基地台邊界移動，相同資料經由空頻編碼或循環延遲調製在相鄰的基地台以相同的頻率傳送，使用者的接收端可以執行天線分集結合的機制獲得分集增益，提供更高的傳輸容量並改善宏觀分集交遞(Macro-Diversity Handover)的效能。
模擬結果顯示，基於降低系統複雜性以及對現存無線通訊系統的兼容性，我們可以選擇採用循環延遲宏觀天線分集結合空間多工機制來改善使用者在基地台邊界面臨傳輸容量不佳的問題。兩種宏觀天線分集結合機制在傳送端天線相關性較低的條件下，能大量改善使用者在基地台邊界的傳輸容量。當傳送天線相關性為0.1時，空頻編碼宏觀天線分集結合空間多工機制可以提供比原先天線之空間多工機制多2 bit/s/Hs的傳輸容量，當傳送天線相關性為0.9時，也還增加0.5 bit/s/Hs的傳輸容量。而循環延遲宏觀天線分集結合空間多工機制當傳送天線相關性為0.1時，可以提供比原先天線之空間多工機制多1 bit/s/Hs的傳輸容量，當傳送天線相關性為0.9時，也還增加0.5 bit/s/Hs的傳輸容量。隨著在基地台傳送天線相關性的增加，仍然可以提供比原本使用天線之空間多工的機制更高的傳輸容量，而且空頻編碼宏觀天線分集結合空間多工機制和循環延遲宏觀天線分集結合空間多工機制之間對傳輸容量改善的差異越來越小。

In the future orthogonal frequency division multiplexing (OFDM) cellular network, base station will adopt multi-input multi-output (MIMO) techniques to improve throughput and link reliability for mobile stations. When the base station using spatial multiplexing (SM) in the downlink case, the throughput of mobile station can be hugely increased nearby the serving base station. However, the total transmit power is split uniformly across the transmit antennas, the signal to interference-and-noise ratio (SINR) degreases with the increasing number of transmit antennas. Additionally, the capacity will seriously decrease at the cell boundary. Thus, SM will reduce the cell coverage in this kind of MIMO OFDM system, the telecommunications operators need to set up more base stations for covering the service areas. This will raise the base station equipment cost of the operators and
increase the handover frequency. In real environment, spatial correlation exists at base station or mobile station due to insufficient antenna separation and the lack of scatter effect. The performance of SM degreases seriously with non-trivial spatial correlation among the transmit antennas, therefore, it becomes a more difficult task to overcome the problem of cell coverage reduced by SM.
In this thesis, we introduce two kinds of macro-diversity combining techniques for spatial multiplexing based MIMO OFDM cellular networks to increase cell boundary throughput and improve soft handover performance. The one is space-frequency block code macro-diversity combining spatial multiplexing scheme. The other is cyclic delay macro-diversity combining spatial multiplexing scheme. Applying transmit diversity at adjacent base station sides and using SM of each base station, we can take both advantages of spatial multiplexing and spatial diversity without increasing the number of transmit antennas or base stations. When a mobile station moves near the cell boundary, the adjacent base stations transmit the same data encoded by SFBC or CDD at the same frequency. At the receiver of the mobile station can perform diversity combining to get the macro-diversity gain, thereby improving throughput and the handover performance.
Because of lower complexity and compatibility to existing wireless communication systems, we conclude that adopting the CDD macro-diversity combining with SM scheme is a preferable scheme to improve the poor throughput of mobile stations near the cell boundary. These two macro-diversity combining schemes can provide a high throughput improvement of mobile station at the cell area in low spatially-correlated channels. As transmit antenna spatial correlation is equal to 0.1, SFBC macro-diversity combining with SM scheme can improve 2 bit/s/Hz more than the conventional SM scheme. As transmit spatial correlation is equal to 0.9, it can still improve 0.5 bit/s/Hz higher than the conventional SM scheme. As transmit antenna spatial correlation is equal to 0.1, CDD macro-diversity combining with SM scheme can improve 1 bit/s/Hz higher than the conventional SM scheme. As transmit spatial correlation is equal to 0.9, it can also improve 0.5 bit/s/Hz more than the conventional SM scheme. With spatial correlation increased at each transmitters of each base station, they also can provide higher throughput than the conventional SM scheme. The variations of throughputs between CDD macro-diversity combining with SM scheme and SFBC macro-diversity combining with SM scheme are getting small at the cell boundary.

Abstract VIII
Acknowledgements X
List of Tables XIII
List of Figures XIV
1 Introduction 1
1.1 ProblemandSolution 2
1.2 Challenges 3
1.3 ThesisOutline 4
2 Background 5
2.1 Macro-Diversity Applications in CDMA and OFDM Systems 5
2.2 Transmit Macro-Diversity Techniques for MIMO OFDM Cellular Mobile Networks 6
2.2.1 Space-Frequency Block Code 7
2.2.2 Cyclic Delay Diversity 8
2.2.3 Comparsion 9
2.3 LiteratureSurvey 10
3 System Model and Problem Formulation 12
3.1 PropagationModel 13
3.1.1 PathLoss 13
3.1.2 Multi-Path Fading Channel Model 14
3.1.3 Spatially-Correlated Rayleigh MIMO Channel 14
3.2 OFDM Signal Model 15
3.2.1 Signal to Interference-and-Noise Ratio 16
3.2.2 Exponential Effective SINR Mapping (EESM) 17
3.3 Problem Formulation 18
4 Space-Frequency Block Code Macro-Diversity Combining for MIMO OFDM Cellular Mobile Networks 21
4.1 SFBC Macro-Diversity Scheme 22
4.2 SINRPerformance 22
4.3 SimulationResults 26
5 Cyclic Delay Macro-Diversity Combining for MIMO OFDM Cellular Mobile Networks 34
5.1 CDD Macro-Diversity Scheme 35
5.2 SINRPerformance 35
5.3 SimulationResults 38
6 Conclusions 46
Bibliography 48
Vita 51

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