An Algorithm for Estimation and Tracking of Distributed Diffuse Scattering in Mobile Radio Channels
Future wireless communication systems will exploit the rich spatial and temporal dispersion of the radio propagation environment. This requires new advanced channel models, which need to be verified by real-world channel sounding measurements. In this context the reliable estimation and tracking of the model parameters from measurement data is of particular interest. In this paper, we build a state-space model, and track the parameters of the distributed diffuse scattering component of the mobile radio channel using the extended Kalman Filter. The extended Kalman Filter is applied to capture the dynamics of the channel parameters in time and to reduce the computational complexity of the estimator compared to existing estimators. The proposed estimator can be combined with existing techniques for the estimation of specular/concentrated propagation paths, which are based on the maximum likelihood approach (SAGE/RIMAX) or the Kalman Filter. The performance of the algorithm is demonstrated using both simulated and measured data
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