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  • 學位論文

多輸入多輸出正交分頻多工系統之訓練型通道估測及功率分配

Training-Based Channel Estimation and Power Allocation for MIMO-OFDM Systems

指導教授 : 蘇炫榮

摘要


這篇論文主要目的是在處理多輸入多輸出正交分頻多工系統下的訓練型通道估測。 我們將依據訓練保護區間來估測通道,這種方法讓接收端能夠從接收信號的一階統計特性,以半盲的方式估測並追蹤通道的變化。相對於傳統中以前置碼估測通道的方法,訓練保護區間並不會降低資訊傳輸率,系統表現也不受限於某些特殊情況下的通道,而比起以二階(或更高階)統計特性或有限字母來估測通道的方法,它所估測出的通道不會被尺度差所模糊。 為了使我們的通道估測均方差最小化,從多根天線傳送出的訓練序列皆必須有脈衝式的自我相關函數,彼此之間的交互相關函數也須為零。我們將藉由一組擁有的零相關區的序列來做為訓練序列,這組序列在某段時間延遲之內滿足上述理想的相關函數特性。 在多天線系統中使用前述訓練序列估測通道,它的表現受限於天線數量及多路徑通道的延遲擴散。為了解決這個問題,我們將訓練序列延長,使它的一部份與資料符元重疊,如此系統將可承受更長的多路徑通道衰減。 另外,由於總傳輸功率固定,我們要處理訓練序列與資料序列間功率配置的問題。藉由評估非理想通道估測對系統表現的影響,我們將找出最好的功率分配以達到最低的字元錯誤率。

並列摘要


This thesis addresses the problem of training–based channel estimation for Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems. We present a channel estimation scheme based on training guard intervals. This way, the receiver can estimate and track the channel variations semi-blindly based on first order statistics of the received signal. There is no extra loss of information rate as opposed to training sequence based methods , no condition imposed on the channel, and no scaling ambiguity as opposed to second (or higher) order statistical or finite alphabet-based methods. To achieve the minimum mean square error, the training sequences transmitted from multiple antennas must have impulse-like autocorrelation functions and zero cross-correlation functions. To this end, we adopt the sequences with Zero Correlation Zone (ZCZ) which possess ideal correlation windows. For multiple-antenna systems, performance of this training scheme will be degraded drastically with the increase of the number of antennas and the delay spreads of multipath channel. We propose to append the training sequences overlapping with data symbols at the transmitter. By this method, the OFDM system can combat longer delay of multipath channel. Moreover, the issue of power allocation between training and information sequences will also be addressed. By evaluating the performance degradation due to imperfect channel estimation, optimal training power overhead that minimizes bit error rate is found.

參考文獻


[1.2] G. B. Giannakis. “Filterbanks for blind channel identification and equalization.”, IEEE Signal Processing Letters , pages 184–187, June 1997.
[1.3] P. Hoeher, S. Kaiser, and P. Robertson. Pilot-symbol-aided channel estimation in time and frequency. GLOBECOM Conference Records (Phoenix, USA), pages 90.96, November 1997.
[1.4] B. Muquet, Marc de Courville,and Pierre Duhamel, ”Subspace-Based Blind and Semi-Blind Channel Estimation for OFDM Systems,” IEEE Trans. on Signal Processing, vol. 50, no. 7, July 2002.
[1.5] B. Porat and B. Friedlander, “Blind equalization of digital communication channels using high-order moments,” IEEE Transactions on Signal Processing, vol. 39, no. 2, pp. 522–526, Feb. 1991.
[1.6] L. Tong, G. Xu, and T. Kailath, “Blind identification and equalization based on second-order statistics: A time domain approach,” IEEE Transactions on Information Theory, vol. 40, no. 2, pp. 340–349, Mar. 1994.

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