本篇論文提出一種適用於多輸入多輸出系統之改良的QRD-M演算法。所謂的QRD-M演算法為藉由QR分解將接收信號表示成樹狀結構後，再搭配M-演算法來執行限制分枝數（或路徑數）的樹狀搜尋。相較於因執行完整樹狀搜尋而具有最佳錯誤率效能表現的最大概似偵測器（MLD），QRD-M偵測器能在錯誤率效能極接近MLD時，大幅度降低完成樹狀搜尋所需執行的實數乘法次數。此演算法結合象限偵測法以及隨著通道環境和功率大小而調整的門檻值來降低樹狀搜尋過程中所需的計算量。設計者可以藉由設定門檻值和選擇象限偵測法之執行象限偵測的次數以求在錯誤率效能和複雜度之間取得折衷。我們對演算法的效能評估是在通道為單一路徑的平坦衰減，並且通道狀況和雜訊功率已被完美估測的假設下。我們比較各種演算法的優劣是基於以下原則：根據電腦模擬結果，我們挑選出在各錯誤率表現圖中之結果皆足夠接近MLD的幾個演算法來比較複雜度。模擬的結果證明：相較於我們主要的比較對象，也就是我們欲改進之現有文獻中的演算法，提出的演算法可明顯降低複雜度。尤其是當字元錯誤率低於 時，此演算法降低複雜度的效果更好。並且當系統使用的調變技術愈高階，愈能有效降低複雜度。

This paper proposes an improved QRD-M detector for multiple input multiple output (MIMO) systems. For the QRD-M detectors, the QR decomposition is used to impose a tree structure in the processed received signal, and the M-algorithm is used to perform the limited tree search. Compared with the optimum ML Detector that performs a full tree search, the QRD-M detector can achieve a similar performance with significantly reduced average number of multiplication operations. The proposed algorithm incorporates quadrant detection and adjustable threshold (for tree pruning) according to the instantaneous channel conditions and the noise power to reduce the computational complexity. By setting an appropriate value for the threshold and selecting the resolution of quadrant detection, the designer can make a desired tradeoff between error rate performance and complexity. We evaluate the performance in flat fading MIMO channels under the assumptions of ideal channel and noise power estimates. Computer simulation results demonstrate that, at the same near-ML performance and compared with previous QRD-M algorithms, the complexity reduction of the proposed algorithm is relatively noticeable. Especially at symbol error rates below , the saving of complexity is more significant when higher modulation schemes are utilized.

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