隨著無線通訊資料傳輸速率需求增高，在傳送端與接收端置放多個天線並使用空間多工 (Spatial multiplexing)是其中一種可以在既定的頻譜範圍內達到此種要求的方法。隨著傳輸容量需求大增，利用增加更多天線數來提高傳輸容量已是趨勢。
由於高維度多入多輸出系統 (MIMO)的要求增加，排序正交三角分解 (sorted-QR decomposition)前置處理在多輸入多輸出偵測法(QR-based MIMO detection)變成一個計算瓶頸，且MIMO detector的功率消耗與計算複雜度呈現巨幅成長。本論文提出的8x8 MIMO detector可分成兩部份。第一部分提出的Givens-Rotation based演算法利用提早停止排列運算機制和放寬執行排序需要成立的條件，進而改善parallel sorted-QR decomposition的吞吐量以及硬體使用效率。偵測效益下降小到可忽略，且在較大天線數時能達到更好的硬體使用效率。第二部分我們提出 8x8 mixed K-best/QR-SIC MIMO detector利用提出的 modified sorted-QR分解做為前置處理。modified sorted-QR利用放寬執行排序需要成立的條件改善運算時間以及硬體使用效率。相對於K-best detector，在高維度 MIMO detection時，我們提出的 mixed K-best/QR-SIC能夠達到更低的計算複雜度而且幾乎沒有偵測效益的損失。

Due to the growing demands of high-dimension multiple-input multiple-output (MIMO)
systems, the preprocessing of sorted-QR decomposition becomes one of the computational
bottlenecks in the QR-based MIMO detection, and the power consumption and
computation complexity of the MIMO detector are growing dramatically. This thesis
proposes an 8 × 8 MIMO detector which can be divided into two parts. First, the
proposed Givens-Rotation-based algorithm aims to improve the throughput and the
hardware utilization efficiency by stopping the sorting operations earlier or relaxing the
sorting condition for the parallel sorted-QR decomposition. The detection performance
degradation is negligible and better hardware efficiency can be obtained for the larger
number of the MIMO antennas. Then, we propose an 8 × 8 mixed K-best/QR-SIC detector
with the proposed modified sorted-QR decomposition as the preprocessing. The
modified sorted-QR decomposition is used to relax the sorting condition to improve the
latency and the hardware utilization rate. Compared to the K-best detector, the proposed
mixed K-best/QR-SIC detector can achieve lower computation complexity with
almost no performance loss in the high-dimension MIMO detection.

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