Precision Measurement and Modeling of Dynamic Millimeter-wave Wireless Propagation Channels

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One of the defining features of 5G communications is the use of frequency bands in the mm-wave range. The ample available bandwidth has the potential to enable dramatically higher data rates, thus enabling a plethora of new applications, ranging from improved video streaming to virtual reality to industrial monitoring and control. However, to properly assess the potential and limitations of such mm-wave systems, it is required to first understand the propagation channel, i.e., the way in which signals propagate from the transmitter to the receiver. Since the fundamental propagation effects such as diffraction and scattering are significantly different at higher frequencies, the overall propagation channel can be expected to be different from the well-explored channels at traditional cellular frequencies. The proposed project will provide a detailed, measurement-based description of mm-wave propagation channels, with special emphasis on the time variations that are created by moving objects (cars, humans, machinery) in the environment. From such understanding, it is possible to obtain insights in how to design more reliable, and more efficient, mm-wave communications systems. Due to the great importance of mm-wave communication, a number of measurements do exist for mm-wave channels, but they show serious restrictions. In particular, no measurements are available that simultaneously (i) provide directional information with high resolution, (ii) are dynamic, i.e., show the impact of moving devices or scattering objects, and (iii) provide a statistically significant number of measurement points that could form a reliable basis of stochastic channel models, or training for machine learning. Because of a lack of measurement results, many assumptions that are used in the development of 5G devices and systems are conjectures, which this project aims to prove or disprove. To achieve this, this project will use a novel channel sounder recently developed at University of Southern California and extend its capabilities through advanced signal processing techniques. This channel sounder is based on the principle of fast beamswitching, which enables high equivalent isotropically radiated power (EIRP) and capturing complete directional channel characteristics within a short time (10ms). Using this sounder, the project will perform and evaluate extensive measurement campaigns, some of which will concentrate on dynamic effects and nonstationarities, while others will exploit the capability for measuring and evaluating massive amount of data. Compared to widely cited existing measurements, the new measurements can be done one million times faster, and three orders of magnitude more measurement locations. Another important result of the project will be the development of new channel models that can reflect all of the relevant channel properties for theoretical analysis as well as system design. By paying attention to the spatial consistency of the results, and analyzing the number and amplitude distribution of the multipath components, better deployment planning, and impact on system performance such as prediction of various beamformer architectures will be enabled.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.