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Frequency domain analysis of the ultrawideband radiowave propagation channel Xin, Ni


The CM 1-8 channel impulse response (CIR) models developed by the IEEE 802.15Aa task group are widely used to fairly compare the performance of alternative UWB signaling schemes under representative line-of-sight and non-line-of-sight conditions in four different environments: residential, office, industrial and outdoor. However, with the advent of MB-OFDM and related schemes, channel frequency response (CFR) models are becoming more pertinent. Here, we show how statistical models of the autoregressive frequency domain (AR-FD) model parameters that estimate for CM 1-8 can be used to gain insights concerning the nature of the channels and efficiently simulate the frequency response of the channels. After generating several thousand instances of the channel response, estimating the AR-FD model parameters for each one, then applying the Akaike Information Criterion (AIC) to determine the appropriate model order, we determine the marginal distributions that best describe each of the AR-FD parameters and their mutual correlation for each of the eight scenarios. We find that the model parameters fall into two independent groups: (1) a set of initial condition parameters that are jointly Gaussian and therefore completely described by their means, variances, and mutual correlation coefficients and (2) a set of parameters that describe the amplitude and phase of the autoregressive poles and the variance of the driving noise and that are described by more exotic distributions. As a result, their mutual correlation is most conveniently described by a copula, a statistical method widely used in finance and finding increasing use in engineering. The result allows us to specify both: (1) a set of statistical parameters that define frequency domain versions of CM 1-8 and (2) a frequency domain channel response simulator. Comparison of the distribution of RMS delay spreads associated with the original training data and simulated channel responses shows good agreement. Further, we demonstrate the utility of the AR-FD approach by using it to interpret UWB channel response data collected within an aircraft passenger cabin and by using AR-FD model parameters as features in the comparison and classification of UWB channel responses collected in different environments.

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