因為行動通訊系統在現今社會已經越來越被廣泛使用，使用無線通訊系統的人口也日益增加，要如何使有限的無線頻譜得以最有效的被利用，是相當重要的課題。Multi-Input Multi-Output(MIMO)接收技術可以有效解決有限頻譜供不應求的問題，MIMO系統可以在頻寬不增加的情況之下進而提升頻譜利用率，解決頻寬不夠的問題。
本篇論文針對大型MIMO接收系統提出新的Sphere Decoding(SD)[1],[2],[3]演算法，主要的目的是要解決SD在多根天線時，系統高複雜度的問題。新的SD演算法主要是結合傳統MMSE-SIC[4]與SD偵測器，並且運用了ML-post detection processing(ML-PDP)的核心精神，先由低複雜度的MMSE-SIC決定可信度不高的位元的位置，然後只將可信度不高的位元送入高複雜度的SD(Sphere Decoder)去做計算，因此大量減少直接將所有的位元放入傳統SD的超高複雜度，模擬顯示在相同的BER條件下，本論文所題出新的SD演算法複雜度比其他現有文獻所提的SD相關技術複雜度，要來的低許多。

Since the mobile communications system as widely used today, the wireless communication system of the population is increasing. How to make the most of limited radio spectrum to be used effectively is a very important issue. Multi-Input Multi-Output (MIMO) receiver technology can effectively solve the problem of the shortage spectrum. MIMO system can solve the problem of insufficient bandwidth without increasing the bandwidth and improve spectrum efficiency.
In this paper, we propose a novel SD algorithm for the large MIMO system. The proposed SD algorithm combines with the MMSE-SIC SISO detection and SD detection. Using the spirit of ML-post detection processing (ML-PDP).Two steps are in the proposed SD algorithm. First, the MMSE-SIC detection is used to obtain the likelihood ratio of the bits. Using the likelihood ratios, the unreliable bits are found and then detected by SD. Because the number of bits detected by SD is reduced, the overall complexity is also reduced. Simulation result shows the proposed SD significantly improves the complexity of conventional SD.

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