垂直貝爾實驗室分層空時(V-BLAST)技術為一種多輸入多輸出(MIMO)的無線系統架構，它可以在低實現複雜度的情況下，達到相當高的頻譜效率。而在本論文中，我們針對V-BLAST正交載波多工(OFDM)系統，提出了一種新型的階層訊號偵測演算法，此種偵測法使用了不同於原先OSIC偵測法的偵法排序。在我們所提出的偵測法中，對於有著最小事後偵測訊雜比(post-detection SNR)的階層，我們使用降低複雜度ML偵測法來偵測，而剩餘的其他階層，我們則是利用降低迭代OSIC偵測法來偵測。最後，經由模擬的結果顯示，我們所提出的偵測演算法，在位元錯誤率方面的效能表現，成功達到逼近最佳的ML偵測法，且在運算複雜度方面，也能有所大幅下降。 Vertical Bell Laboratories Layered Space-Time(V-BLAST) is a multiple-input multiple-output(MIMO) wireless system. V-BLAST attains very high spectral efficiency while maintaining a low complexity of implementation. In this thesis, we propose a new layered symbol detection algorithm for V-BLAST OFDM systems. The proposed algorithm uses a symbol detection ordering method which is different from that recommended in the original OSIC algorithm. In our scheme, for the layer with the smallest post-detection SNR, we use reduced complexity ML for detection, and for other layers, a reduced iterative OSIC detection scheme is developed. Simulation results show that the proposed detection algorithm achieves high detection performance which is close to the ML detection method, and significantly reduces the computational complexity.
