在多細胞多天線的分時雙工無線網路當中，通道狀態的資訊是藉由所有在網路裏的使用者，傳送彼此正交的上行領航訊號(Pilot Signal)，並在基地台端估計而得。由於在細胞網路當中，為了提高頻譜的使用效率，相同頻段的頻譜在不同細胞之間會重複使用，且正交的領航訊號個數有限，與整個同調時間(coherent time block)長短有關；導致相同的領航訊號也會被其他細胞的用戶重複使用，這些非正交領航訊號使得通估計不準確，被其他細胞裡使用相同領航訊號使用者的通到干擾了，這便是領航訊號污染的問題。
在此論文當中，我們提出一領航訊號傳送的排程方法，並在接收端作適當的接收訊號運算，使得領航訊號污染的問題可以完全消除。進一步地使用最小平方通道估計器來估計原本的目標通道以及干擾通道。此一通道估計的方法是即時進行的，基地台不需要等的整個傳送領航訊號的週期結束後才進行通道估測。由於使用最小平方通到估計器，我們不需假設已知所有通道的統計特性。在得到估計通到後，我們使用Zero-Forcing預編碼的方法分析下行資料傳送時，每個使用者所能達到的傳輸速率。除了下行資料傳輸外，由於我們的方法可於基地台端取得干擾通道的資訊，故於上行資料傳輸時，基地台可以利用這些資訊幫助基地台端消除來自於其他細胞使用者的干擾訊號，讓使用者資料的解碼更為準確。

In the multi-cell large-scale antenna TDD networks (Massive MIMO TDD networks), the channel state information (CSI) is explored by using uplink training sequences (pilots) which are transmitted by users during the training time. Due to the frequency reuse in the cellular networks and the finite length limit of pilot sequences (depending on the length of channel coherent time), the pilot sequences used in co-channel cells are unavoidable to be non-orthogonal. That is to say, the same set of pilot sequences is reused among the cells, which causes the pilot contamination problem.

In this thesis, we propose a new pilot transmission scheduling scheme to completely eliminate the pilot contamination. Further, we apply least-square (LS) channel estimator to derive the estimates of both desired channels and inter-cell interference (ICI) channels, so that we do not need to know the second order statistics of channels. Besides the desired channel estimate, the ICI channel estimate also can be obtained in the this scheme. The achievable rate of downlink data transmission by Zero-Forcing (ZF) precoding is also analysed. Besides downlink data transmission, we use the estimates of interfering channels to help the base station when decoding the symbols users transmit during uplink data transmission.

Chinese Abstract i
English Abstract ii
Contents iii
1 Introduction 1
2 System Description 5
2.1 Uplink Training and Channel Estimations . . . . . . . . . . . . . . . . . . . 6
2.1.1 Least-Square (LS) Channel Estimator . . . . . . . . . . . . . . . . . 7
2.1.2 Linear Minimum Mean Square Error (LMMSE) Channel Estimator . 7
2.2 Normalized Mean Square Error (NMSE) of Estimators . . . . . . . . . . . . 9
3 Communication Scheme 11
3.1 Round Robin Pilot Transmission . . . . . . . . . . . . . . . . . . . . . . . . 12
3.2 Successive Pilot Contamination Elimination Scheme [1] . . . . . . . . . . . . 15
3.2.1 Estimator 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
iii
3.2.2 Estimator 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.3 Proposed Uplink Training Scheme . . . . . . . . . . . . . . . . . . . . . . . . 18
3.3.1 Estimation of Desired Channels . . . . . . . . . . . . . . . . . . . . . 20
3.3.2 Estimation of Inter-Cell Interference (ICI) Channels . . . . . . . . . . 23
3.4 Downlink Data Transmission . . . . . . . . . . . . . . . . . . . . . . . . . . 25
3.4.1 Zero-Forcing (ZF) Precoding . . . . . . . . . . . . . . . . . . . . . . 25
3.4.2 Achievable Rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
3.5 Uplink Data transmission . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
4 Simulation Results 30
4.1 Normalized Mean Square Error of Estimated Channel . . . . . . . . . . . . . 30
4.2 Uplink Data Transmission with ZF Detection . . . . . . . . . . . . . . . . . 36
5 Conclusions 39

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