Modeling the statistical time and angle of arrival characteristics of an indoor multipath channel

Abstract

Abstract-Most previously proposed statistical models for the indoor multipath channel include only time-of-arrival characteristics. However, in order to use statistical models in simulating or analyzing the performance of systems employing spatial diversity combining, information about angle of arrival statistics is also required. Ideally, it would be desirable to characterize the full space-time nature of the channel. In this paper, a system is described that was used to collect simultaneous time and angle of arrival data at 7 GHz. Data processing methods are outlined, and results obtained from data taken in two different buildings are presented. Based on the results, a model is proposed that employs the clustered "double Poisson" time-of-arrival model proposed by Saleh and Valenzuela (1987). The observed angular distribution is also clustered with uniformly distributed clusters and arrivals within clusters that have a Laplacian distribution.

Multipath channel identification by using global optimization in ambiguity function domain

“…The clusters are attenuated in amplitude and path arrivals within a single cluster also have amplitudes decayed with patterns that are exponential with time and are parameterized with two time constants; the cluster arrival decay time constant and the ray/multipath arrival decay time constant. A space-time statistical model is presented as an extension of the time-only model of [45] in [46]. In [47], authors make use of the recent advances in the theory of compressed sensing, to formalize the notion of clustered multipath sparsity and to exploit delay, Doppler and spatial diversity.…”

“…Recent multipath channel measurement results show that multipath components are distributed in as clusters within a defined channel spread and impinge onto a receiver in clusters [5,[45][46][47]. In [45], a statistical model, which is based on only temporal clustering structure they observed in their indoor multipath data, is presented.…”

A robust iterative algorithm for wireless MIMO array auto-calibration

“…. , Nr}, when minimizing v 2 2 . This is particularly true when false DOAs are picked up in phase I so that no good κ match is available.…”

“…Scatter plots of calibration estimates for 1000 randomly generated complex gain vectors, κ m. Estimated calibration gains are shown relative to the true values (i.e.κm/κm is plotted). The random channel realizations were generated with an accurate cluster-based multipath model [2]. It can be seen that a bias towards zero in the gain magnitudes has been eliminated by using the RIMM constraint.…”

“…A number of researchers have reported on channel probing experiments to characterize MIMO channel statistics, evaluating such physical characteristics as multipath ray structure, angle spread, delay spread, raypath clustering, and array correlation [2] [3]. Estimating these channel features requires accurate knowledge of array parameters such as element locations and complex gain responses.…”