Fast solution of 5G channel path loss in substation based on improved ray tracing method.

Area of Science:

• Electrical Engineering
• Signal Processing
• Wireless Communications

Background:

• Fifth-generation (5G) signals require efficient channel path loss computation due to high frequencies and large computational scales.
• Traditional algorithms face high complexity when calculating dyadic reflection-diffraction coefficients for 5G channel path loss.

Purpose of the Study:

• To develop a fast solution method for 5G channel path loss in substations.
• To reduce the computational complexity of 5G channel path loss calculations using singular value decomposition.

Main Methods:

• Utilized the ray tube model to segment the channel and discard redundant or low-contribution incident angle information.
• Applied singular value decomposition (SVD) for matrix dimensionality reduction.
• Substituted the reduced matrix into the sum-vector inverse wrap-around coefficient formula for fast path loss calculation.

Main Results:

• The proposed method achieved an accuracy loss of only 1.31%.
• Data compression reached 84.89%.
• Computational complexity was reduced by 10^5 orders of magnitude compared to traditional algorithms.

Conclusions:

• The singular value decomposition-based method offers a computationally efficient and accurate solution for 5G channel path loss.
• This approach enhances the adaptability of channels to signal receivers, ensuring 5G signal reception quality.
• Future work includes real-time data integration and extension to sixth-generation (6G) and beyond.