English

A Framework for Developing and Evaluating Algorithms for Estimating Multipath Propagation Parameters from Channel Sounder Measurements

Signal Processing 2023-10-16 v1

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 omnidirectional 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 singlesnapshot maximum likelihood estimation problem: greedy matching pursuit (CLEAN), space-alternative generalized expectationmaximization (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.

Keywords

Cite

@article{arxiv.2310.08718,
  title  = {A Framework for Developing and Evaluating Algorithms for Estimating Multipath Propagation Parameters from Channel Sounder Measurements},
  author = {Akbar Sayeed and Damla Guven and Michael Doebereiner and Sebastian Semper and Camillo Gentile and Anuraag Bodi and Zihang Cheng},
  journal= {arXiv preprint arXiv:2310.08718},
  year   = {2023}
}

Comments

17 pages

R2 v1 2026-06-28T12:49:17.643Z