5G Positioning Via AoA and ToA Estimates in Secondary Airports
Yesilyurt, Ismail Taylan (2023)
2023
Master's Programme in Electrical Engineering
Informaatioteknologian ja viestinnän tiedekunta - Faculty of Information Technology and Communication Sciences
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Hyväksymispäivämäärä
2023-05-22
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202305165837
https://urn.fi/URN:NBN:fi:tuni-202305165837
Tiivistelmä
Positioning parts within Advanced-Surface Movement Guidance and Control Systems (A-SMGCS) is challenging for the current positioning technologies due to strict availability, reliability, and update rate requirements. In addition, the high cost of existing A-SMGCS solutions used in primary airports has made it challenging for secondary (small to medium-sized) airports to implement these systems. Therefore, cost-efficient alternative positioning techniques for secondary airports are an essential area of research in the aviation sector.
The fifth-generation network 5G has significant potential as a low-cost solution for these airport positioning scenarios considering their large-scale deployment in the near future. This master’s thesis focuses on 5G time of arrival (TOA) and angle of arrival (AOA) positioning performance analysis for downlink (DL) and uplink (UL) direction through MATLAB simulations with various channel models combined with line-of-sight (LOS) and non-line-of-sight (NLOS) propagation scenarios. In the simulations, Positioning Reference Signal (PRS), Sounding Reference Signal (SRS), and Channel State Information Signal (CSI-RS) which are the reference signals standardized for 5G, are used. TOA estimates are calculated using correlation results with reference signals assuming the receiver has prior information about reference signal configurations. AOA estimates are computed by processing phased array antenna outputs by subspace-based Multiple Signal Classification (MUSIC) AOA estimation algorithm. To analyze the effect of noise and multipath on positioning performance, average white Gaussian noise (AWGN) channel, 5G Tapped Delay Line (TDL) models, 5G Clustered Delay Line (CDL) models, and WINNER II channel models are employed.
The findings indicate that the designed solution based on the 5G reference signals has a significant potential for secondary airport positioning. Also, the impact of various factors such as 5G signal configurations, multipath, and NLOS transmission are analyzed.
The fifth-generation network 5G has significant potential as a low-cost solution for these airport positioning scenarios considering their large-scale deployment in the near future. This master’s thesis focuses on 5G time of arrival (TOA) and angle of arrival (AOA) positioning performance analysis for downlink (DL) and uplink (UL) direction through MATLAB simulations with various channel models combined with line-of-sight (LOS) and non-line-of-sight (NLOS) propagation scenarios. In the simulations, Positioning Reference Signal (PRS), Sounding Reference Signal (SRS), and Channel State Information Signal (CSI-RS) which are the reference signals standardized for 5G, are used. TOA estimates are calculated using correlation results with reference signals assuming the receiver has prior information about reference signal configurations. AOA estimates are computed by processing phased array antenna outputs by subspace-based Multiple Signal Classification (MUSIC) AOA estimation algorithm. To analyze the effect of noise and multipath on positioning performance, average white Gaussian noise (AWGN) channel, 5G Tapped Delay Line (TDL) models, 5G Clustered Delay Line (CDL) models, and WINNER II channel models are employed.
The findings indicate that the designed solution based on the 5G reference signals has a significant potential for secondary airport positioning. Also, the impact of various factors such as 5G signal configurations, multipath, and NLOS transmission are analyzed.