本論文的目標是提出了一種用於多根天線通訊系統之低計算量最大事後機率軟決策輸入軟決策輸出偵測器。我們所提出的低計算量最大事後機率軟決策輸入軟決策輸出偵測器的基礎在於接受端的信號看成高斯複數隨機變數。我們提出兩種方法來降低偵測器的計算量。第一種方法針對接受信號的共變異數矩陣做簡化，第二種方法利用遞歸方程式來取代最大事後機率的積分。模擬結果顯示我們所提出的低計算量偵測器接近最佳效能而且計算量比所有其它偵測器還低，例如比最常用的 minimum mean-square error with soft interference cancellation (MMSE-SIC) 軟決策輸入軟決策輸出偵測器低 24 倍。除此優點以外我們所提出的偵測器利用比較穩健的數值運算方法。低計算量及穩健的數值運算使我們所提出的偵測器可以在硬體上實現。

This thesis proposes a low-complexity maximum a posteriori probability (MAP) soft-in soft-out (SISO) detector for multiple-input multiple-output (MIMO) communication systems. Our low-complexity MAP SISO detector is based on the assumption that the received signal has a joint complex Gaussian probability density function (PDF). We propose two methods to reduce computational complexity. The first method simplifies the computation of the covariance matrix of the received signal. The second method introduces a recursive formula which substitutes the integration of the maximum a posteriori probability. Simulation results show that the proposed low-complexity MAP SISO detectors approach optimum performance, which is obtained with the conventional MAP SISO detector. Moreover, the computational complexity of our proposed detectors are much lower than those of other SISO detectors. For example, its computational
complexity is 24 times lower than the minimum mean-square error with soft interference cancellation (MMSE-SIC) SISO detector, which is the most commonly used detection algorithm. It also uses more stable numerical methods which, coupled with lower computational complexity, enable hardware implementation.

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