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Title: Improving Channel Gain Cartography via Side Information
Committee:
Dr. Weitnauer, Advisor
Dr. Li, Chair
Dr. Durgin
Abstract:
The motivation of this work has been the optimization of cognitive radio networks, based on real-time measured channel information. The purpose of the proposed dissertation is to explore algorithms to predict the path loss between transceivers at proposed arbitrary locations in a network, given certain channel characteristics measured between transceivers at other known locations in the network. Names for this problem include RF mapping, radio map interpolation, spectrum cartography, channel gain cartography, and channel gain mapping. The measured channel characteristics considered in this dissertation include the line of sight power and the powers and excess delays of the non-line-of-sight paths of propagation, for the purpose of locating reflecting and therefore shadowing objects in the environment. There are two existing approaches to channel gain mapping that both use only the LOS component. One, by the research group of Giannakis, takes a purely statistical approach and decomposes the cost function into a low rank component and a sparse component. The other is a proof of optimal estimation that requires more restrictive assumptions than Giannakis. One approach we plan to investigate is to modify the Giannakis cost function to include the side information we glean from the measurements. The dissertation will com- pare the new and state-of-the art algorithms using computer simulation as well as measured ultra-wideband channels.
