Performance Analysis for Path Attenuation Estimation of Microwave Signals Due to Rainfall and Beyond
Boming Song, Defeng David Huang, Xi Shen, Roberto Togneri
Abstract
The attenuation of microwave signals can be used for meteorological observations. For example, the received signal level (RSL) of backhaul links of cellular systems, which usually has a quantization error of 0.1 dB or more for commercial systems, has been used to measure rainfall. In this work, through the mean square error (MSE) analysis of an ideal RSL estimator, it is found that the estimation error can be lower than 0.01 dB for high signal-to-noise ratio (SNR), thereby making it feasible to measure other meteorological variables such as water vapor and clouds. However, the RSL-based estimator has poor performance in low SNR. To improve the performance, we propose a new path attenuation measurement method based on SNR estimation. Although the performance of the SNR-based estimator is better than the RSL based one for low SNR, it becomes worse in high SNR when the path attenuation is small. To solve the problem, another method is proposed based on estimating the signal power (SP) only. Both MSE analysis and simulation results show that the SP-based method is superior to both RSL and SNR based estimators for most scenarios.
BibTeX
@inproceedings{icassp2020_performanceanaly,
title = {Performance Analysis for Path Attenuation Estimation of Microwave Signals Due to Rainfall and Beyond},
author = {Boming Song and Defeng David Huang and Xi Shen and Roberto Togneri},
booktitle = {ICASSP 2020},
year = {2020}
}