Joint Communication and Positioning Based on Soft Channel Parameter Estimation
A joint communication and positioning system based on maximum likelihood channel parameter estimation is proposed. The parameters of the physical channel, needed for positioning and the channel coefficients of the equivalent discrete time channel model, needed for communication are estimated jointly using a priori information about pulse shaping and receive filtering. The paper focuses on the positioning part of the system. It is investigated how soft information for the parameter estimates can be obtained. On the basis of confidence regions, two methods for obtaining soft information are proposed. The accuracy of these approximate methods depends on the nonlinearity of the parameter estimation problem, which is analyzed by so called curvature measures. The performance of the two methods is investigated by means of Monte Carlo simulations.