應用於OFDM信號偵測之盲目資料偵測演算法研究

OFDM信號通常是以加入一段嚮導信號(pilot signal)來提供接收端作通道估測(channel estimation)之用，並進一步估測出原來的傳送信號，然而加入的嚮導信號卻必須佔用珍貴的頻寬，限制了可傳送的資料量，造成頻寬的使用效率降低。因此在本篇論文裡，我們引用了線性規劃的概念來解決信號估測的問題，並且針對衰減通道 (fading channel)，使用數學複雜度較低的least-square (LS) 的通道估測法，推導出遞迴關係式，再使用branch-and-bound (B&B) 演算法進行最佳解搜尋，以此方式執行訊號估測的好處是我們不但無須在傳送端加入嚮導信號，也可以在接收端估測出原來的傳送訊號，進而增加頻寬的使用效率。在本篇論文裡討論了兩種演算法的實現方式，並且在比較過後決定採用鏈結串列 (linked-list) 的方法來作模擬，使用這個方法可以早期刪除無用的解碼樹的分枝，以避免展開所有的樹上的節點，這個方法所找到的解也保證是最佳的而不是次佳的解。

關鍵字

盲目資料偵測；鏈結串列；分支界限演算法

並列摘要

Orthogonal frequency-division multiplexing (OFDM) systems use the pilot signals to estimate the channel, and restore the received signals to the original signals. But the pilot signals will occupy the bandwidth, limit the transmitting data rate, and make the bandwidth low efficiency. We apply the method of linear programming to solving this signal estimation problem in a fading channel, and then convert the problem into one that finds the sequence x that minimizes least-square (LS) channel estimation function and then get the regression formula. We apply the branch-and-bound (B&B) algorithm to finding the optimum solution. The advantage is that the pilot signals can be illiminated for estimating the channel and the transmitted information can be recovered.. In this thesis, by using the linked-list method, the B&B algorithm is implemented. It can discard the branches of the useless decoding tree earlier, and that is not necessary to expand all the branches to find the optimal solution, and the solution should be the best solution.

並列關鍵字

B&B ； Blind estimation ； linked-list

參考文獻

[2]Michael Honig, Upamanyu Madhow, Sergio Verdo, “Blind Adaptive Multiuser”, IEEE Trans. Information Theory, Vol. 41, pp.944-960, 1995

[3]Ming-Xian Chang, Yu T. Su, “Blind and Semiblind Detections of OFDM Signals in Fading Channels”, IEEE Trans. Communication. Vol. 52, pp.744-754, 2004.

[4]Ming-Xian Chang, Yu T. Su, “2-D regression channel estimation for equalizing OFDM signals”, IEEE 51st Vehicular Technology Conf. pp. 240-244, 2000

[5]Marc Engels, Wireless OFDM Systems:How to make them work?, Kluwer Academic Publishers, 2002

[6] J. B. McQueen (1967): "Some Methods for classification and Analysis of Multivariate Observations", Proceedings of 5-th Berkeley Symposium on Mathematical Statistics and Probability, Berkeley, University of California Press, 1:281-297

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應用於OFDM信號偵測之盲目資料偵測演算法研究

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