針對多輸入多輸出(multiple-input multiple-output, MIMO)的線性非時變(linear time invariant, LTI)系統，祁等人提出一個高運算效率之快速峰度最大化演算法(Fast Kurtosis Maximization Algorithm, FKMA)。此演算法係一個疊代批次處理演算法且已被應用於盲蔽訊號源分離(blind source separation, BSS)或獨立成份分析(independent component analysis, ICA)。本論文考慮多用戶正交分頻多工系統(Orthogonal Frequency Division Multiplexing, OFDM)之盲蔽波束成型。假定在一個正交分頻多工區塊中通道是靜止不變的，基於在一個正交分頻多工區塊之子載波平均，再藉由峰度最大化法進而提出一個盲蔽波束成型演算法，包含了訊號抽取、時間延遲估計和補償、以及分類和盲蔽最大比值合併(Blind Maximum Ratio Combining, BMRC)。對所有的子載波而言，所設計之波束成型器都是相同的，並有效地利用多路徑分集以獲得效能增益，同時對存在相關性訊號之影響具有強健性。一些模擬結果被呈現驗證所提出之盲蔽波束成型演算法之功效。

Chi et al. proposed a computationally efficient fast kurtosis maximization algorithm for multiple-input multiple-output linear time-invariant systems. This algorithm is an iterative batch processing algorithm and has been applied to blind source separation (or independent component analysis). This paper considers blind beamforming of multiuser orthogonal frequency division multiplexing (OFDM) systems. Assuming that the channel is static within one OFDM block, a blind beamforming algorithm by kurtosis maximization based on subcarrier averaging over one OFDM block is proposed, which basically comprises source extraction, time delay estimation and compensation, and classification and blind maximum ratio combining. The designed beamformer is exactly the same for all the subcarriers, effectively utilizes multipath diversity for performance gain, and is robust against the effects of correlated sources. Some simulation results are presented to demonstrate the effectiveness of the proposed blind beamforming algorithm.

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