基於毫米波頻段巨量天線第五代蜂巢式系統中手機同步及基地台搜尋方法之研究

A Study on Handset Synchronization and Cell Search Methods for 5G Cellular System based on Massive Antennas in Millimeter Wave Band

林秉儒

5G ； 細胞搜尋 ； 同步 ； OFDM ； 5G ； Cell Search ； Synchronization ； OFDM

交通大學電信工程系所學位論文

2016年

碩士

黃家齊

英文

在第五代蜂巢式系統下，使用者手機開機會面臨同步和基地台搜尋的問題，在本篇論文中，我們提出了新的方法進行同步和基地台搜尋。本論文研究第五代蜂巢式系統下的基地台搜尋程序，我們會分成不同階段來進行討論。我們利用時域和頻域分別進行使用者資料傳輸和基地台搜尋程序，彼此之間的影響和效能會在本文中討論。在第一階段，我們利用在時域上所接收到的訊號進行我們所提出演算法來估計符元時間和小數載波頻率偏移，這種方法是不需要使用任何額外已知的訊號去做互相關運算。在第二階段，我們利用在頻域上擁有最大能量的主控制頻的位置來偵測整數載波頻率偏移。在第三階段，校正完整數載波頻率偏移後，我們利用第二大能量的輔控制頻的位置來獲得細胞基地台的識別碼。在第四階段，我們利用輔控制頻所攜帶的控制訊號做差分檢測來判斷是否為訊框起始位置。在進行這四個階段後，使用者手機就可以完成同步和基地台搜尋。在模擬結果中，我們所提出估計時間和小數載波頻率偏移的演算法優於傳統的同步方法。在時域上存在使用者資料的干擾下，我們利用頻域的控制頻去偵測整數載波頻率偏移與細胞基地台的識別碼及訊框起始位置方法的效能都能達到我們的需求。

In the 5G cellular system, there exists the problem of synchronization and cell search when the mobile boots up. In this thesis, we propose a new method to execute synchronization and cell search. The cell search procedure is discussed and is divided into four different stages in the 5G cellular system. The users' data signals are transmitted in the time domain and we execute cell search according to control signals transmitted in the frequency domain at the same time. In the first stage, we use the received signal with the proposed algorithm to estimate symbol timing and fractional carrier frequency offset (FCFO) in the time domain, this method does not require any additional preamble to do cross correlation. In the second stage, we use a primary control tone to detect integer carrier frequency offset (ICFO) in the frequency domain. In the third phase, we use the secondary control tones to obtain cell ID after adjustment of ICFO. In the fourth stage, we use the control data, which is carried by the secondary control tones, to detect frame header by differential detection. The cell search procedure ends when the above four stages are completed. In our simulation results, we show that the proposed joint symbol timing, FCFO estimation, cell ID detection, and frame header detection algorithms have superior performances even with the interference of users' data.

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