Power Delay Profile Based Ranging via Approximate EM-ReVAMP

Abstract

Accurate distance estimation is of utmost importance in enabling seamless positioning and location-based services for 5G and Beyond 5G (B5G) networks. This paper focuses on addressing the ranging problem caused by multipath propagation, utilizing the widely adopted Nakagami-m amplitude fading model. We propose a novel method for estimating range based on Multipath Components (MPCs), establishing a relationship between the distribution parameters and propagation distance. To address the estimation problem within the MPCs-based ranging method, we employ the Expectation Maximization (EM)-Revisited Approximate Message Passing (ReVAMP) algorithm. This algorithm is specifically designed to handle challenges in parameter estimation for generalized linear models (GLMs) with hidden random variables and intractable posterior distributions during EM iterations. Simulation results have been conducted to prove the accuracy and robustness of our ranging method, which consistently confirm its effectiveness.