正交分頻多重存取（orthogonal frequency division multiple access，OFDMA）上傳系統在現今的無線通訊領域上被廣泛應用。正交分頻多重存取技術結合了正交分頻多工技術（orthogonal frequency division multiplexing，OFDM）與分頻多重存取（frequency division multiple access，FDMA）的概念，將頻譜上所有的子載波（subcarrier）劃分成數個不重複的子集合或子頻帶，並將每個子頻帶指派給不同的使用者，利用子載波之間的正交性（orthogonality）來傳輸不同類型的資料。由於都普勒效應與載波震盪器不精準所造成的使用者頻率偏移會破壞子載波之間的正交性，而對每個使用者造成多重存取干擾，導致系統位元錯誤率效能下降。文獻上提出許多干擾壓抑或干擾消除的方法來解決多重存取干擾造成的影響，然而完成干擾壓抑或干擾消除的前提是使用者頻率偏移已知，因此多使用者頻率偏移估測成為正交分頻多重存取上傳系統中的重要課題。
本篇論文提出了適用於可加性高斯白雜訊通道下的最小均方差準則估測法來完成頻率偏移估測。最小均方差準則估測法藉由修正了[9]的干擾壓抑權重係數，透過頻率偏移測試參數來搜尋使用者頻率偏移，當頻率偏移測試參數等於使用者頻率偏移時，修正後的干擾壓抑權重係數能發揮最佳地干擾壓抑的功能而分離出觀察使用者的估測訊號，此時估測訊號在星座圖上每個象限的分布是最密集的，因此在任一象限上會有最小的均方差。相較於多重訊號分類估測法[12]或旋轉不變性參數估測法[13]的估測方法，必須利用延長循環字首的方法來處理使用者滿載的問題，這個作法會造成多餘的功率消耗或是降低資料吞吐率，最小均方差準則估測法的優點在於，使用者頻率偏移在頻率偏移測試參數的搜尋範圍內，即使不延長循環字首，無論使用者個數為何，都可以找到符合均方差有最小的頻率偏移測試參數為使用者頻率偏移估測值。模擬結果顯示，使用者未滿載時，系統均方差的效能在高訊雜比時優於[12]與[13]的演算法，而使用者滿載時，也有可以接受的系統均方差的效能。

Orthogonal Frequency Division Multiple Access (OFDMA) uplink systems have been adopted generally in wireless communication in recent years. By combining Orthogonal Frequency Division Multiplexing (OFDM) with Frequency Division Multiple Access (FDMA), OFDMA systems divide all subcarriers in frequency domain into several mutually exclusive subbands, and assign the subbands to different user, transmitting different kinds of data by the orthogonality between subcarriers. The users’ Carrier Frequency Offsets (CFO) caused by Doppler effects and/or misadjusted local oscillators may destroy the orthogonality between subcarriers, then lead to Multiple Access Interference (MAI) for all users, the MAI may degrade the performance of bit error rate. Several MAI suppression or cancellation schemes have been investigated to mitigate the effect of MAI, however, these schemes work on the hypothesis of known CFOs. As the result, it is the crucial issue for the multiuser CFOs estimation in OFDMA uplink systems.
In this paper, we propose the Minimum Mean Square Error Criterion (MMSEC) estimation scheme to achieve multiuser CFOs estimation in Additive White Gaussian Noise (AWGN) environment. By modifying the MAI suppression weighting in [9], the MMSEC scheme search desired user’s true CFO with CFO trial parameter, while the CFO trial parameter is equal to true CFO, the modified MAI suppression weighting will suppress the MAI ideally and then separate the desired user’s estimated signal from received signal. Thus the distribution of estimated signal is highly concentrated in each of quadrant in the signal constellation, and it will have the minimum mean square error in each of quadrant. Compare with the MUtiple SIgnal Classification (MUSIC) scheme [12] and the Estimation of Signal Parameter via Rotational Invariance Technique (ESPRIT) scheme [13], they deal with the fully loaded problem by extending cyclic prefix, that may cause the redundant power consumption or degrade data throughput, the advantage of the MMSEC scheme is that it can works on fully load without extending cyclic prefix. Because despite fully loaded, the CFO trial parameter search desired user’s true CFO in reasonable range until it causes minimum mean square error. The simulation result shows that the non-fully loaded system mean square error (MSE) performance is superior to the MUSIC and ESPRIT schees at high signal to noise ratio, while system is fully loaded, the system MSE performance is also acceptable.

誌謝 i
摘要 iii
Abstract iv
目錄 vi
圖索引 viii
第一章 簡介 1
第二章 系統模型 5
2.1 正交分頻多工存取的上傳系統模型 5
2.2 頻率偏移的影響 7
第三章 多重存取干擾壓抑 11
3.1 考慮使用者子載波交錯式配置 11
3.2 多重存取干擾壓抑的原理及架構 15
第四章 頻率偏移估測 19
4.1 多重訊號分類估測法 19
4.2 旋轉不變性參數估測法 22
4.3 最小均方差準則估測法 24
4.3.1 最小均方差準則 24
4.3.2 使用者滿載之分析 26
4.3.3 干擾壓抑權重係數的修正 35
第五章 系統模擬 38
5.1 收集正交分頻多工存取區間個數之探討 38
5.2 頻率偏移、目前使用者個數、最大使用者個數與子載波個數之影響 40
5.3 與多重訊號分類估測法的均方差比較 45
第六章 結論 49
附錄A 自相關矩陣R理論值 50
參考文獻 53

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