Electromagnetic Vector Antenna Array-Based Multi-Dimensional Parameter Estimation for Radio Propagation Measurement | IEEE Journals & Magazine | IEEE Xplore

Electromagnetic Vector Antenna Array-Based Multi-Dimensional Parameter Estimation for Radio Propagation Measurement


Abstract:

A multi-dimensional parameter estimation method for radio propagation measurements is investigated. A distributed electromagnetic vector antenna (EMVA) array-based multip...Show More

Abstract:

A multi-dimensional parameter estimation method for radio propagation measurements is investigated. A distributed electromagnetic vector antenna (EMVA) array-based multiple signal classification (MUSIC) method is proposed to estimate the delay, the angle of arrival (AoA), and the cross polarization ratio (XPR) of every ray. The delay is estimated using the channel response matrix. After the polarization smoothing, the AoA is estimated. Applying the spatial smoothing method, the XPR is then obtained. Simulation results reveal that using the proposed multi-dimensional parameter estimation method, more rays with higher accuracy can be estimated than the ones using the conventional method.
Published in: IEEE Wireless Communications Letters ( Volume: 8, Issue: 6, December 2019)
Page(s): 1608 - 1611
Date of Publication: 26 July 2019

ISSN Information:

Funding Agency:

No metrics found for this document.

I. Introduction

To design and evaluate a mobile communication system, a channel model that can capture channel characteristics is essential [1]. The clustered delay line (CDL) channel models, defined for the full frequency range from 0.5 GHz to 100 GHz with a maximum bandwidth of 2 GHz, are mostly used for link-level simulations [2]. Channel realizations are generated by summing contributions of rays with specific channel parameters like delay, power, angle-of-arrival (AoA), cross polarization ratio (XPR), etc. These parameters are all random and their probability distributions come from radio propagation measurements [3].

Usage
Select a Year
2025

View as

Total usage sinceJul 2019:408
01234JanFebMarAprMayJunJulAugSepOctNovDec233000000000
Year Total:8
Data is updated monthly. Usage includes PDF downloads and HTML views.

References

References is not available for this document.