NB-IoT Uplink Vector Signal Generator and Analyzer Design and NPRS Based OTDOA Positioning

• Main Authors: Yen-Ju Yao, 姚彥如
• Other Authors: Jeng-Kuang Hwang
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/33meqy

碩士 === 元智大學 === 通訊工程學系 === 106 === 3GPP completed the NB-IoT R14 standard in June 2017. The IoT service of telecom operators has been officially transferred, and NB-IoT has begun to flourish. Since both R&D and mass production require expensive equipment to verify their products. Therefore, in this thesis we have designed the uplink vector signal generator (VSG) and analyzer (VSA) algorithms according to NB-IoT R14 physical layer (PHY) specification. Then combined with the software-defined radio (SDR) platform, our testing platform can even achieve a performance close to commercial instruments, making it attractive for industrial applications. The contribution of this study can be divided into four parts. First, we generate the NB-IoT uplink signal in software, and actually transmit the RF signal on the SDR platform composed of the instrument and MATLAB. We then verify the correctness of the signal by commercial VSA. Secondly, we consider the actual RF transmission problem, and design the uplink VSA algorithm operating on the SDR platform. From the EVM results and comparison with the commercial VSA, it shows that our VSA performs close to the expensive commercial VSA. Thirdly, we study the synchronization problem for superimposed NPRACH (Narrowband Physical Random Access Channel) preambles under multi-UE case. Low-complexity algorithm for estimating the RCFO (residual carrier frequency offset) and ToA (Time of Arrival) parameters is developed, and it can even outperform the existing method in [1]. Finally, according to the new downlink narrowband positioning reference signal (NPRS) of NB-IoT R14, we propose a low-complexity frequency-domain ToA estimation method for the hyperbolic positioning of UE based on OTDoA (Observed Time Difference of Arrival). As compared to the conventional time domain cross-correlation ToA estimation method, the proposed method not only eliminates the discrete grid problem in positioning coordinates, but also has significantly better positioning accuracy within 50m, as shown by the simulation results under the Rician fading, EPA (Extended Pedestrian A model), and ETU (Extended Typical Urban model) channels.