- 學位論文
利用Simulink－Zedboard SDR共模擬設計具效率式FIR濾波器架構之5G NR細胞搜尋過程
Co-Simulation Design Based on Simulink-Zedboard SDR for 5G NR Cell Search Procedure with Efficient FIR Filter Architecture
摘要
自從2019年上半年韓國和美國啟動了5G新無線電（New Radio, NR）的商業營運，我國緊接著也在2020年1月最終發布了5G NR的釋照，並於2020年下半年開始商業運營。此外，行政院也於2019年開始提出為期四年的二百億計畫用來開發5G NR核心技術以及5G NR系統測試平台，加速我國研發能力以成為世界5G NR供應鏈中的重要合作國家。 本論文依照5G NR之3GPP-v16工作標準[1]以及根據低複雜度高精確度5G NR細胞搜尋演算法[2]，並利用Simulink-Zedboard 軟體定義無線電(Software-Defined Radio, SDR)共模擬方式，來設計具效率式有限脈衝響應(Finite-Length Impulse Response, FIR)濾波器架構之5G NR細胞搜尋過程。文獻[2]的特點為，(1)使用平均式時頻估測演算法以提昇時頻參數估測的精確性，(2)利用頻域相關性運算降低細胞搜尋過程的運算量。因此文獻[2]的演算法即使在極低訊雜比(Signal-to-Noise Ratio, SNR) SNR=-6dB以及在嚴峻通道環境ETU300之下，仍可超過70%細胞搜尋偵測率，達到商用的要求[2]。 在本論文，吾人使用Simulink-Zedboard SDR共模擬設計方法，以快速雛型化具效率式FIR濾波器架構之重要核心元件。在細胞搜尋過程演算法的設計上，分成四個流程，(1)使用平均式時頻估計演算法估測粗符碼時間與分數載波頻偏(Fractional Carrier Frequency Offset, FCFO)，(2)偵測5G NR之主要同步訊號起始(Primary Synchronization Signals, PSS)的起始位置，(3) 估測整數CFO (integer CFO, ICFO)與扇形細胞索引(sector cell index, S-CID)，以及(4)估測出分群細胞識別碼(group cell identity, G-CID)。在實現上，吾人參考文獻[16,17]並依照演算法每一部分的需求來設計出具高效率之FIR濾波器架構。在論文中所使用具高效率之FIR濾波器架構，共有Type-I、Type-II以及Type-III三種不同架構。在第四章會有深入的介紹以及比較。此外，在考量比較上的公平，吾人選用常見的橫向(transversal) FIR濾波器架構作為對照組。最後，Zedboard硬體實現與Simulnik軟體設計的二者共模擬設計結果十分接近，驗證硬體設計的穩定性與正確率。
並列摘要
Since South Korea and United States initialize the commercial operation for 5G New Radio (NR), our country in turn release the licenses of 5G NR in January 2020 and then start the commercial operation at second half of year 2020. Moreover, the Executive Yuan have launched a four-year plan of 20 billion dollars to develop critical 5G NR technique and 5G NR system test platform. In doing so, our country can be expected to be the key partner of the 5G-NR supply chain in the world. In this thesis, we present the Simulink-Zedboard software-defined radio (SDR) hardware implementation for the 5G NR cell search procedure with efficient finite-length impulse response (FIR) filter architecture. In the design, we follow the 3GPP-v16 working standard for 5G NR [1] and employ the cell search algorithm with low computing complexity and high accuracy [2]. The primary characterizations of the algorithm in [2] are stated as follows: (1) The high-accuracy time-average timing-frequency estimation is employed to enhance the cell index detection rate greatly, and (2) The high cell index detection rate up to 70% can still be accomplished even though under the extremely low signal-to-noise ratio (SNR) of SNR = -6 dB and severe channel environment with ETU300 channel model. In doing so, the commercial requirements can be achieved. In the thesis, we employ the co-simulation design method with Simulink-Zedboard SDR platform quickly to implement the prototypes of the important devices of the 5G-NR cell search procedure with efficient finite-impulse-response (FIR) architecture. In the design of the 5G-NR cell search procedure algorithm, the flowchart is divided into four parts. First, estimate the coarse symbol timing and the fractional carrier frequency offset (FCFO) by using the time-averaged time-frequency parameters estimation algorithm. Second, detect the starting position of the 5G-NR Primary Synchronization signal (PSS). Third, detect the integer CFO (ICFO) and the sector cell index (S-CID) simultaneously. Finally, detect the group cell identity (G-CID). In the implementation, we use the algorithm proposed in [16] and [17] as a basis to design the cell search procedure with the highly efficient FIR filter architecture. In this thesis, we present three different types of the highly efficient FIR architecture types, including Type-I, Type-II, and Type-III. The three FIR types, which are discussed and compared in Chapter 4. Besides, the transversal FIR filter architecture is considered for fair comparison. Finally, the co-simulation design results of Zedboard hardware design and the software Simulink design are consistent well with each other. It is showed that the hardware design is correct and stable.
參考文獻
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