ation properties, not Doppler profiles [BrDe91]. short data intervals render non-physical channel states The measurements were recorded in a hall of 15 [Kott04]. As additive noise reduces the achievable Propagation modelling and channel characterisation CHAPTER 4.7 Unitary-ESPRIT Root-MUSIC Large room NLoS Large room LoS Mod. Covariance Corridor Floor Urban industrial Urban town squares Urban street NLoS Urban street LoS Urban Suburban hilly Suburban Rural hilly Rural QR-RLS Reliable envelope prediction range (2) (a) Various synthetic channel scenarios. Scenario RX-1 Unitary-ESPRIT Scenario RX-2 Root-MUSIC Mod. Covariance QR-RLS Reliable envelope prediction range (A) (b) Measured indoor data. Figure 4.7-47 Extrapolation lengths for various synthetic channel scenarios and for measured indoor data, for prediction schemes based on Unitary ESPRIT, root-MUSIC and several AR-based schemes (see text) (after [SeKa03]). prediction length too, practical prediction lengths with broadband processing by taking the frequency de- prediction schemes based on subspace spectral estimators pendence of the Doppler shifts and the time de- will be limited to less than a wavelength, a conclusion pendence of the delays into account [Semm04b]. In his earlier reached by Teal [Teal01]. two-point analysis, these dependences were estimated In this respect, Jakes models with nine (angularly) by applying a 2D ESPRIT routine twice, at different well-separated deterministic Doppler components are measurement times. Later on even a 4D SAGE was used ideally suited for subspace-based spectral estimators, as al- on a slightly different formulation, estimating delay, ready noted by Semmelrodt and Kattenbach [SeKa03], Doppler, and the time gradients of both [Semm04b]. and using these models for evaluation of fading prediction These approaches were abandoned with the success of performance [SeKa03], [DuHH00], [Ekma02] is likely to the much simpler AR-based prediction on narrowband give far too optimistic results as compared to realistic channels descri