祁等人提出一個快速峰度最大化演算法(Fast Kurtosis Maximization Algorithm, FKMA)於多輸入多輸出(Multiple Input Multiple Output, MIMO)線性非時變系統的盲蔽等化/反旋積(blind equalization/deconvolution)中。這個演算法已經被應用於單速率直接序列/分碼多工存取(Direct Sequence/Code Division Multiple Access, DS/CDMA)系統的盲蔽多用戶檢測(blind multiuser detection)以及盲蔽訊號分離(blind source separation)或者獨立元素分析(independent component analysis)。在本篇論文中，快速峰度最大化演算法更進一步應用於多速率直接序列/分碼多工存取系統之盲蔽多用戶檢測，此想法是藉由轉換真實多速率使用者成多個單速率虛擬使用者(virtual users)以建立離散時間多輸入多輸出信號模型，並且使用快速峰度最大化演算法抽取出想要的虛擬使用者的資料序列，並將這些估測出的虛擬使用者資料序列還原想要的使用者資料序列。本論文中，假設所有使用者的展頻序列(spreading sequences)都事先已知，我們提出一個基於瞬時(instantaneous)多輸入多輸出信號模型的多速率盲蔽多用戶檢測演算法(結合單一或多接收天線)，此演算法享有快速峰度最大化演算法的超指數收歛速度以及保證收斂之優點。最後，呈現一些模擬結果以驗證所提出的演算法之功效，並與現存一些演算法的性能做比較。

Chi et al. proposed a fast kurtosis maximization algorithm (FKMA) with computationally efficient for blind equalization/deconvolution of multiple input multiple output (MIMO) linear time-invariant systems. This algorithm has been applied to blind multiuser detection of single-rate direct sequence/code division multiple access (DS/CDMA) systems and blind source separation (or independent component analysis). In this paper, the FKMA is further applied to blind multiuser detection for multi-rate DS/CDMA systems. The ideas are to formulate discrete-time MIMO signal models by converting real multi-rate users into single-rate virtual users, followed by the use of FKMA for extraction of virtual users’ data sequences associated with the desired user, and recovery of the data sequence of the desired user from estimated virtual users’ data sequences. Assuming that all the users’ spreading sequences are given a priori, the proposed multi-rate blind multiuser detection algorithm (with either a single receive antenna or multiple antennas), which based on an instantaneous MIMO signal model, enjoys the merits of super-exponential convergence rate and guaranteed convergence of the FKMA. Finally, some simulation results are then presented to demonstrate the efficiency and to provide a performance comparison with some existing algorithms.

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