本篇論文將提出一個名為“序列高斯近似信息疊代搭配前綴線性濾波”(Successive Gaussian Approximation based Belief Propagation detection with linear pre-filtering) 的多用戶檢測技術，此多用戶檢測技術可適用於新無線存取方案。透過非正交技術及多用戶過載傳輸，新無線存取方案有能力支援第五代行動通訊系統的需求。序列高斯近似信息疊代的概念在於將干擾及雜訊項近似為一個高斯隨機變數，接著重複進行多次疊代信息，其中在每一次的疊代中，信息是依序被更新，透過這樣的方式，能在接收端複雜度不很高的前提下，讓信息被有效率且準確地傳遞。在本篇論文中探討了兩個新無線存取技術的候選方案，用來評估序列高斯近似信息疊代檢測的效能及潛力，本篇論文亦將序列高斯近似信息疊代檢測和高斯近似信息疊代檢測及最小均方差估測搭配序列干擾消除進行比較，模擬結果顯示序列高斯近似信息疊代檢測和高斯近似信息疊代檢測相比下有著更好的效能，並在多用戶共享存取系統中，序列高斯近似信息疊代檢測也優於最小均方差估測搭配序列干擾消除。因應未來大量連結的需求，本篇論文也探討了高負載用戶的條件以及基地台搭配多接收天線的模擬，並再一次驗證了序列高斯近似信息疊代搭配前綴線性濾波的潛力。

In this thesis, we propose a multi-user detection (MUD) technique called “Successive Gaussian Approximation based Belief Propagation (SGA-BP) detection with linear pre-filtering”, which can be applied to the new radio multiple access (NR-MA) schemes. With the use of non-orthogonal technique and overloaded transmission, NR-MA schemes have capability to support the requirements of the 5G wireless systems. The concept of SGA-BP detection is to approximate the interference-plus-noise term as a Gaussian random variable and perform iterative SGA-BP, where messages are updated successively during each iteration. By doing so, messages can be delivered efficiently and accurately with low computational complexity. In this thesis, we discuss two candidate schemes of NR-MA to evaluate the performance and potential of SGA-BP detection. We also compare the SGA-BP detection with the GA-BP detection and the minimum mean square error (MMSE) successive interference cancellation (SIC) detection. Simulation results show that SGA-BP detection achieves better performance than the GA-BP detection, and outperforms the MMSE-SIC detection when applied to the MUSA system. For the requirements of massive connections, we also discuss the cases of high overload conditions and a BS with multiple antennas, and again verify the potential of SGA-BP detection with linear pre-filtering.

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