Multipath Component Power Delay Profile Based Ranging

Precision ranging technology has become indispensable for ensuring efficient, reliable, and low-latency fifth-generation (5G) networks. In this paper, we propose a novel ranging method which is multipath component (MPC) power delay profile (PDP) based ranging. Whereas the Received Signal Strength (R...

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Veröffentlicht in:IEEE journal of selected topics in signal processing Jg. 18; H. 5; S. 950 - 963
Hauptverfasser: Xiao, Fangqing, Zhao, Zilu, Slock, Dirk T. M.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.07.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Accuracy
Algorithms
Approximation algorithms
Attenuation
Computer Science
Delay
Delays
Direction-of-arrival estimation
Distance measurement
expectation maximization
Fading
Fading channels
Hardware
Message passing
Multipath channels
multipath component
Network latency
Numerical models
Parameter estimation
Parameter modification
power delay profile
Random variables
Ranging estimation
revisited vector approximate message passing algorithm
Signal processing algorithms
Signal strength
Simulation
Power Delay Profile
Multipath Component
Revisited Vector Approximate Message Passing Algorithm
Expectation Maximization
Ranging Estimation
ISSN:1932-4553, 1941-0484
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Zusammenfassung:Precision ranging technology has become indispensable for ensuring efficient, reliable, and low-latency fifth-generation (5G) networks. In this paper, we propose a novel ranging method which is multipath component (MPC) power delay profile (PDP) based ranging. Whereas the Received Signal Strength (RSS) only summarizes the PDP into a single characteristic, we aim to furthermore exploit the range dependent curvature of the PDP envelope over its delay spread. However, the multipath propagation only allows to sample the PDP envelope at the path delays and suffers from (slow) fading. Hence our approach involves constructing a statistical fading model of the PDP and establishing a relationship between the distribution parameters and the propagation distance. To theoretically validate the feasibility of our proposed method, we adopt the widely accepted Nakagami-m fading model, which renders traditional estimation methods difficult to apply. Therefore we introduce the Expectation Maximization (EM)-Revisited Vector Approximate Message Passing (ReVAMP) algorithm. This algorithm is specifically designed to handle difficulties in parameter estimation for Gaussian linear models (GLMs) with hidden random variables and intractable posterior distributions. Extensive numerical simulation results have been conducted which exhibit preliminary evidence of the effectiveness of our MPCPDP-based ranging method compared to the received signal strength (RSS)-based method. Moreover, the versatility of the EM-ReVAMP algorithm allows for its extension to other statistical fading models beyond the Nakagami-m model with minor modifications, which opens the door to potential improvements based on more accurate statistical fading models. Nevertheless, the applicability of our MPCPDP-based ranging method should be validated in real-world scenarios in future studies.
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ISSN:1932-4553
1941-0484
DOI:10.1109/JSTSP.2024.3491580