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

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 <inline-formula><tex-math notation="LaTeX">$\text {wideband}$</tex-math></inline-formula> measurements. We also derive the theoretical bias of this <inline-formula><tex-math notation="LaTeX">$\text {estimator}$</tex-math></inline-formula> and find it depends jointly on the <inline-formula><tex-math notation="LaTeX">$\text {number}$</tex-math></inline-formula> of <inline-formula><tex-math notation="LaTeX">$\text {channel}$</tex-math></inline-formula> transfer function envelope samples across the <inline-formula><tex-math notation="LaTeX">$\text {measurement}$</tex-math></inline-formula> bandwidth, the correlation among such samples, and the K-factor values. Qualitative analysis indicates that the bias increases nearly linearly with the K-factor (<inline-formula><tex-math notation="LaTeX">$K\geq 1$</tex-math></inline-formula> 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.