多重輸入多重輸出技術是一種用來描述多天線無線通訊系統的數學模型,利用在發射端的多根天線各自獨立地發送訊號,同時在接收端也利用多根接收天線並且恢復資訊。
多重輸入多重輸出技術可以在不需要增加頻寬或者總發射功率耗損的情況下大幅增加系統的資料吞吐量以及傳送的距離。多重輸入多重輸出技術的核心概念為利用多根發射天線與多根接收天線所提供之空間自由度來有效提升無線通訊系統之頻譜效率，以提升傳輸速率並改善通訊品質。
若能搭配適當的訊號偵測演算法必能有效地提升頻譜使用效率,但是效能較佳的演算法往往會伴隨著高複雜度的問題,例如能夠達到最大概似解的球體解碼演算法,雖然能達到最大概似解,但是其複雜度為指數成長,複雜度還是太過龐大。
在本論文裡,我們提出了一種利用差分度量的偵測演算法。使用差分度量可以在搜尋的過程中只用到加法而不需要使用乘法,但是必須要有一些前置的運算量。基於差分度量,我們進一步提出梯度演算法加上我們所設計的搜尋停止機制;也就是修正的梯度演算法來達到近似最大概似解。後來基於差分度量的特性,提出了指標演算法,他能夠在做梯度搜尋之前,先確定起始序列的某些位元是否為最大概似解位元,之後再去做更高階的梯度搜尋,能夠更進一步地減少複雜度。

The multiple-input multiple-output (MIMO) technology is a model that can be used to describe the multiple antenna wireless communication system. MIMO can significantly increase the throughput and the transmitted distance without increasing the bandwidth and the total transmitted power.
It can effectively increase the spectrum efficiency with appropriate detection algorithm.
But usually, the good performance may be with more computational complexity, like the Sphere Decoding (SD). The SD can attain the maximum likelihood (ML) solution, but the computational complexity increases exponentially in low and medium SNRs.
In our thesis, we studied a detection algorithm based on the differential metric. The searching process only needs additions. But there are some pre-processes. Based on the differential metric, we studied the gradient algorithm with stop condition, so called the modified gradient algorithm to reach the near-ML performance. Based on the properties of the differential metric, we further studied the indicative functions. It can help us to determine the ML bits in the updated initial sequence before the higher order gradient search. By doing so, it can reduce the computational complexity.

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