多重輸入多重輸出技術可以讓頻譜使用更有效率並且增加通訊的吞吐量，但也因此增加接收端偵測器的複雜度。球體解碼演算法雖然提供一個有效率的方法來得到最大概似解，但它的複雜度依然太高。在本篇論文中，我們提出利用差分量度的一種偵測器演算法。
利用差分量度可以進一步的把乘法變成加法運算因而減少複雜度，但我們需要多餘的事前運算。然而在非時變通道或是通道變化較慢的情況下，我們可以減少使用差分量度球體解碼的事前運算量。我們提出梯度演算法，利用差分量度可以減少偵測器的複雜度。梯度演算法加上我們所設計的能量停止機制，可以獲得接近最大概似解的效能並且大大減少複雜度，可以在效能和複雜度之間取得平衡。最後一個章節探討梯度演算法的各種不同的變化，可以再次減少偵測器的複雜度。

The multiple-input multiple-output (MIMO) technology can make full use of the spectrum and increase the communication throughput. The sphere decoding (SD) algorithm provides an efficient way to obtain the optimal maximum-likelihood (ML) detection. However, the SD algorithm are of much higher complexity, especially at lower signal-to-noise ratio.
In this thesis, we propose efficient detection algorithms for the MIMO system based on the differential metrics. We first give an efficient recursive calculation for the differential metrics of different orders. Based on the differential metrics, we propose the gradient search algorithm, in which the operation of multiplication in double formats is only necessary ahead of the searching process. During the searching process, we need only the operation of addition. We further propose a gradient search algorithm with a stop condition, which can provide a trade-off between performance and complexity.

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