長期演進技術 (Long Term Evolution， LTE) 為第四代行動通訊技術 (The Fourth Generation of Mobile Phone Mobile Communication Technology Standards， 4G) 的標準，在下行鏈路 (Downlink) 採用正交分頻多工 (Orthogonal Frequency Division Multiplexing， OFDM) 並結合多輸入多輸出 (Multiple Input Multiple Output， MIMO) 技術，能夠滿足行動裝置下載大量資訊的需求。
行動裝置開發初期可以透過電腦模擬進行效能的評估，但隨著行動通訊傳輸速率大幅提升，龐大的資料量將導致電腦模擬時間過長，需要耗費大量的時間等待模擬結果。本論文以多核心電腦形成平行處理架構，並搭配數學核心庫 (Math Kernel Library， MKL) 及單指令流多資料流 (Single Instruction Multiple Data， SIMD) 加快基頻處理的運算速度，所涉及的演算法包括同步搜尋、通道估測及多輸入多輸出檢測器，我們將研究成果以 Linux 軟體平台實現，整體資料處理的時間能夠接近實時 (Real Time)。

Long-term-evolution (LTE) and LTE-Advance are undoubtedly the most successful mobile broadband technologies in the fourth generation (4G) wireless system. LTE employs orthogonal frequency division multiplexing (OFDM) and multiple input multiple output (MIMO) technologies in the downlink, which can provide the demand of mobile device with high data rate.
Performances of a mobile device can be evaluated by using software simulations in early development. However, processing the massive amounts of data shall become more and more time-consuming as the data transmission rate continuously increases with the development of communication. In this thesis, we aim to use multi-core computer to speed up LTE baseband processing by math kernel library (MKL) and single instruction multiple data (SIMD). The involved baseband algorithms include synchronization search, channel estimation, and multiple input multiple output detector. We implement the LTE software platform on the Linux platform and show that the processing time can close to real-time.

第一章緒論 1
1.1 研究背景 1
1.2論文構 2
第二章長期演進技術介紹 3
2.1正交分頻多工原理 4
2.4 長期演進技術訊框 7
2.4.1循環前綴 7
2.4.2 傳輸資源區塊 9
2.4.3 LTE實體層訊號 10
2.5 同步搜尋 12
2.6通道估測 13
2.7多輸入多輸出檢測器 14
2.8 平行處理 14
2.9 數學核心庫 15
2.10單指令流多資料流 16
第三章 實時LTE訊號處理架構 18
3.1傳送端 18
3.2接收端 19
3.2.1 RTO環境設定 20
3.2.1 資料擷取至記憶體 21
3.2.2 資料傳輸 21
3.2.3輸入至軟體平台 22
3.3軟體接收機 22
3.3.1同步搜尋 22
3.3.2子訊框分配 24
3.3.3通道估測 25
3.3.4 MIMO 檢測器 27
第四章 結果分析 32
4.1 Windows 系統軟體平台 32
4.2 Linux 系統軟體平台 33
4.3不同系統平台與實時處理比較 36
第五章 結論 37
參考文獻 38
附錄 期望傳播演算法程式碼 40

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