Estimation of the K-Factor for Temporal Fading From Single-Snapshot Wideband Measurements

Abstract

The Ricean K-factor is the ratio of the power of the deterministic multipath component (MPC) and the power of all other stochastic MPCs. The classical moment-based method has been successfully used to estimate the K-factor from time series measurements. In this paper, we apply this method to estimate the K-factor for narrowband temporal selectivity, based upon the analysis of frequency-selectivity in single-snapshot $\text {wideband}$ measurements. We also derive the theoretical bias of this $\text {estimator}$ and find it depends jointly on the $\text {number}$ of $\text {channel}$ transfer function envelope samples across the $\text {measurement}$ bandwidth, the correlation among such samples, and the K-factor values. Qualitative analysis indicates that the bias increases nearly linearly with the K-factor ( $K\geq 1$ on the linear scale) and is affected by correlation amongst the samples. Furthermore, the bias is inversely proportional to the number of samples. Simulations confirm the validity of the derivations. Moreover, a measurement campaign is designed at 28 GHz with a system bandwidth of 400 MHz in an urban micro-cell scenario. The proposed estimator is used to extract the statistics of the K-factor in line of sight and non-line of sight scenarios. The relationship between the K-factor and distance is investigated and a linear model is used to characterize it.