A Framework for Developing Algorithms for Estimating Propagation Parameters from Measurements

TL;DR

This paper introduces a comprehensive framework for developing and evaluating algorithms that estimate multipath propagation components in millimeter-wave environments, using an idealized model and new error metrics.

Contribution

It proposes an idealized measurement model, a new angle-delay representation, and evaluation metrics, along with initial results for a greedy matching pursuit algorithm for MPC extraction.

Findings

Greedy-LS algorithm effectively extracts MPCs over a large dynamic range.

The framework enables systematic evaluation of MPC estimation algorithms.

Results suggest potential improvements by extending the greedy-LS algorithm and integrating features from other methods.

Abstract

A framework is proposed for developing and evaluating algorithms for extracting multipath propagation components (MPCs) from measurements collected by sounders at millimeter-wave (mmW) frequencies. To focus on algorithmic performance, an idealized model is proposed for the spatial frequency response of the propagation environment measured by a sounder. The input to the sounder model is a pre-determined set of MPC parameters that serve as the "ground truth." A three-dimensional angle-delay (beamspace) representation of the measured spatial frequency response serves as a natural domain for implementing and analyzing MPC extraction algorithms. Metrics for quantifying the error in estimated MPC parameters are introduced. Initial results are presented for a greedy matching pursuit algorithm that performs a least-squares (LS) reconstruction of the MPC path gains within the iterations. The results indicate that the simple greedy-LS algorithm has the ability to extract MPCs over a large dynamic range, and suggest several avenues for further performance improvement through extensions of the greedy-LS algorithm as well as by incorporating features of other algorithms, such as SAGE and RIMAX.