Maximum likelihood channel parameter estimation from multidimensional channel sounding measurements

We describe a multidimensional maximum likelihood estimator for radio channel parameters. We also derive a data model to describe the complete data, which is virtually applicable to every antenna array geometry. The proposed iterative gradient based algorithm has been developed, since algorithms using component-wise updates of the likelihood function show a slow convergence, if at least two propagation paths with nearly the same parameters exist in the measured radio propagation paths with nearly the same parameters exist in the measured radio propagation scenario, that means if super-resolution is necessary. The algorithm provides furthermore a variance estimate of the estimated parameters, since the Fisher-information matrix is calculated throughout the algorithm.