A Novel Time Delay Estimation Algorithm for 5G Vehicle Positioning in Urban Canyon Environments.

Area of Science:

• Electrical Engineering
• Wireless Communications
• Signal Processing

Background:

• Global Navigation Satellite Systems (GNSS) struggle with positioning in urban canyons.
• 5G offers potential for vehicle positioning but suffers from ranging errors due to non-line-of-sight (NLOS) propagation.
• Accurate time delay estimation is crucial for advanced 5G positioning techniques.

Purpose of the Study:

• To develop a novel time delay estimation algorithm for 5G vehicle positioning in urban canyons.
• To address and mitigate ranging errors caused by NLOS propagation in 5G signals.
• To enhance the overall positioning accuracy of 5G-based vehicle systems.

Main Methods:

• Proposed a new algorithm: Non-Line-of-Sight Cancellation Multiple Signal Classification (NC-MUSIC).
• Employed cross-correlation to identify and cancel NLOS signals.
• Utilized unsupervised multipath estimation to determine multipath numbers and extract the noise subspace for MUSIC spectral analysis.
• Simulated using the 3GPP TR38.901 5G channel model.

Main Results:

• The NC-MUSIC algorithm demonstrated significant advantages in mitigating NLOS propagation effects in urban canyon simulations.
• Achieved high-precision time delay estimation for direct path signals.
• The algorithm's performance was validated under challenging urban canyon conditions.

Conclusions:

• The NC-MUSIC algorithm provides a robust solution for precise time delay estimation in 5G vehicle positioning.
• It significantly improves positioning accuracy in urban canyons by overcoming NLOS propagation challenges.
• Enables enhanced performance for positioning methods like Observed Time Difference of Arrival (OTDOA) and Angle of Arrival (AOA) ranging.