A Genetic Algorithm Based Iterative Channel Estimation Method for Ranging Applications in Closely-Spaced Multipath Environment

Radio based positioning using terrestrial radio signal like 5th-Generation (5G) technology has attracted attention in past years, which strongly depends on the accuracy of the channel path parameter estimation. In real wireless propagation environment, the transmitted signal undergoes complex propag...

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Bibliographic Details
Published in:IEEE antennas and wireless propagation letters 2025-01, p.1-5
Main Authors: Lyu, Yue, Xue, Bingjie, Wang, Wei
Format: Article
Language:English
Subjects:
Accuracy
Antenna measurements
Channel estimation
Channel parameter estimation
Delay estimation
Distance measurement
Encoding
genetic algorithm
Genetic algorithms
Genetics
multipath
OFDM
Parameter estimation
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Summary:Radio based positioning using terrestrial radio signal like 5th-Generation (5G) technology has attracted attention in past years, which strongly depends on the accuracy of the channel path parameter estimation. In real wireless propagation environment, the transmitted signal undergoes complex propagation phenomenons including reflection, diffraction and scattering. The multipath propagation, particularly in the dense multipath environment, significantly impact the ranging accuracy. Traditional maximum likelihood methods like the space-alternating generalized expectation-maximization (SAGE) suffer from the closely-spaced multipath. In this letter, we propose a genetic algorithm (GA) based channel parameter estimation method for closely-spaced multipath environment. The paths' parameters are first encoded into binary code space in which the possible solutions are searched towards the optimum. Both simulation and measurement based results reveal that the delay estimation performance of the proposed method is superior to that of the SAGE algorithm when paths are closely-spaced.
ISSN:1536-1225
1548-5757
DOI:10.1109/LAWP.2025.3535561