近年來的無線通訊系統中，資料傳輸的速率以及連線品質受到越來越高的要求，而能夠提供較佳傳輸效率與連線可靠度的多輸入多輸出(multiple-input multiple-output, MIMO)傳輸方式，也漸漸吸引許多研究開發的目光。然而要如何使用較有效率的方式實現多輸入多輸出偵測器，也成為多輸入多輸出系統開發的重要課題。
本篇論文主要利用非排序演算法(sort-free)與提出之平均值輔助預先刪除技術(mean-aided early-pruned)實現多輸入多輸出偵測器。此偵測器能夠在保持傳統非排序演算法的效能下，進一步降低運算的節點數目。由實驗結果可以顯示出，所提出之可重組4×4多輸入多輸出偵測器在同樣系統參數下，與現有文獻相比能夠達到較好的正規化吞吐量(normalized throughput)，在節點運算方面與傳統非排序演算法和K-Best演算法相比也能達到明顯的降低。

For recent years, wireless communication networks are increasingly required to provide high data rate and high link quality. Multiple-input multiple-output (MIMO) transmission techniques which can offer high spectral efficiency and improved link reliability have become more attractive by researchers. The main challenge of the practical realization of MIMO wireless communication systems is how to implement the MIMO detector efficiently.
This work presents a MIMO detector based on the sort-free concept and the proposed mean-aided early-pruned scheme. The derived MIMO detector can reduce the number of node computation while maintaining the bit error rate (BER) performance of the conventional sort-free MIMO detection algorithm. Experimental results shows that the proposed reconfigurable detector design with 4×4 antenna array has better normalized throughput rate compared to those of existing detectors under the same system configurations. Moreover, a significant reduction on node extensions can be achieved using the presented detection scheme compared with the conventional sort-free algorithm and the K-best algorithm.

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