학술논문

A Framework for Developing and Evaluating Algorithms for Estimating Multipath Propagation Parameters From Channel Sounder Measurements
Document Type
Periodical
Source
IEEE Transactions on Wireless Communications IEEE Trans. Wireless Commun. Wireless Communications, IEEE Transactions on. 23(5):4424-4441 May, 2024
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Signal Processing and Analysis
Mathematical models
Antenna measurements
Frequency measurement
Estimation
NIST
Data models
Wireless communication
Antenna arrays
antenna radiation patterns
beamspace processing
CLEAN algorithm
high-resolution algorithms
maximum likelihood (ML) estimation
millimeter-wave (mmWave) measurements
multidimensional signal processing
multipath propagation channel models
parameter estimation
RiMAX algorithm
space-alternative generalized expectation-maximization (SAGE) algorithm
Language
ISSN
1536-1276
1558-2248
Abstract
A framework is proposed for developing and evaluating algorithms for extracting multipath propagation components (MPCs) from measurements collected by channel sounders at millimeter-wave frequencies. Sounders equipped with an omni-directional transmitter and a receiver with a uniform planar array (UPA) are considered. An accurate mathematical model is developed for the spatial frequency response of the sounder that incorporates the non-ideal cross-polar beampatterns for the UPA elements. Due to the limited Field-of-View (FoV) of each element, the model is extended to accommodate multi-FoV measurements in distinct azimuth directions. A beamspace representation of the spatial frequency response is leveraged to develop three progressively complex algorithms aimed at solving the single-snapshot maximum likelihood estimation problem: greedy matching pursuit (CLEAN), space-alternative generalized expectation-maximization (SAGE), and RiMAX. The first two are based on purely specular MPCs whereas RiMAX also accommodates diffuse MPCs. Two approaches for performance evaluation are proposed, one with knowledge of ground truth parameters, and one based on reconstruction mean-squared error. The three algorithms are compared through a demanding channel model with hundreds of MPCs and through real measurements. The results demonstrate that CLEAN gives quite reasonable estimates which are improved by SAGE and RiMAX. Lessons learned and directions for future research are discussed.