n schemes like Unitary ESPRIT and root-MUSIC are preferred. They also perform well with Figure 4.7-46 Principle of fading prediction based on spectral stochastic (outdoor) channels with relatively few and estimators. The measured complex fading signal (top, solid, magnitude shown) is decomposed in complex sinusoidal com- separated scatterers but showed mediocre performance ponents (bottom, solid, real part shown). These are extrapolated with the indoor measurements. Schemes that work on beyond the measurement interval (bottom, dotted) and combined a fixed delay and Doppler grid, like EM-based methods, into the fading signal prediction (top, dotted). do in general not have enough resolution to produce any useful prediction. Therefore, Semmelrodt and Katten- stemming from important reflections in the environment bach suggest that the adaptive filter approach is preferred, with different angles of arrivals. In the case of narrow- giving the best results in realistic scenarios and being of band prediction, the individual delays of the components (significantly) less computational complexity than the are only visible as additional phase shifts. In practice, this spectral estimators [SeKa03]. Also, extension to wide- approach does not model the numerous small compo- band prediction schemes is relatively straightforward. nents attributed to diffuse scattering, the curvature of the wavefronts of the Doppler components, and Error sources in narrowband fading prediction non-stationary channel states. Kotterman investigated the accuracy of narrowband fading prediction for synthetic channels, consisting of Narrowband fading prediction deterministic Doppler components of random shifts, with Semmelrodt and Kattenbach made an extensive survey of prediction algorithms built around subspace-based spectral estimators for prediction algorithms [SeKa03]. parameter estimator schemes like ESPRIT, root-MUSIC, They compared spectral estimators based either on and some derivatives [Kott04]. His conclusion was that spectral search (MUSIC 