Characterization and parameterization of dynamic wireless channels over long duration using evolutionary channel parameters

Abstract

Summary The characterization and parameterization of processes that arise in many fields of science and technology are very crucial. Of particular importance are dynamic processes whose statistics are time‐varying and are often modeled as stochastic processes. A typical example of such process is the wireless communication channel. Existing methods that are used to characterize and parameterize the dynamic stochastic wireless channel often consider short‐term duration over which the channel statistics are invariant. Conversely, this paper presents the characterization of the dynamic wireless communication channel over a long‐term duration where time/frequency channel realizations are obtained at sample intervals. To structure such channel realizations over a long duration, the idea of concatenating the ‘instantaneous’ channel realizations is presented. The resultant concatenated multivariable process is characterized using the concepts of process non‐summability and piecewise separability. Based on these concepts, the second‐order statistical parameterization of the concatenated stochastic process in both time and frequency domain is presented. The parameterization approach is based on fitting appropriate set of unit step functions that approximate the raw concatenated data using sets of evolutionary stationarity parameters. To illustrate the concepts developed in this paper, measurement‐based experiments and analysis are presented and adaptively applied to improve wideband multicarrier system performance. Copyright © 2015 John Wiley & Sons, Ltd.

Channel measurement and time dispersion analysis for outdoor mobile ultrawideband environment

“…In all existing literature, the analysis of time dispersion characteristics of the UWB channel does not include stationarity attributes of measured data. This paper differs significantly from our earlier work on the characterization and parameterization of dynamic wireless channels using evolutionary channel parameters [19] in that it focuses on the time dispersion analysis of UWB channel measurements in two separate outdoor mobile scenarios. Hence, the following are our major contributions in this paper:…”

“…In the case of the recreation park scenario, channel parameter values may vary from one sitting location to another, and from one position to another as a user walks around the park. The worst-case scenario approach is always used for conventional system design when choosing effective system parameter values from the channel measurement results [19]. This pessimistic approach may simplify the design of transceivers, but merely assures average performance, since resources are often underutilized.…”