In wireless communication systems, the direct signal andthe reflected signals form an interference pattern resulting in a received signal given by the sum of these components. They are distinguished by their Doppler shifts at the mobile. Since the parameters associated with these components are slowly varying, the fading coefficients can be accurately predicted far ahead. We introduced a novel algorithm for long range predictionof fading channels. This algorithm finds the linear Minimum MeanSquared Error (MMSE) estimate of the future fading coefficientsgiven a fixed number of previous observations. We show that thesuperior performance of this algorithm is due to its longer memoryspan achieved by using lower sampling rate given fixed model orderrelative to the conventional (data rate) methods of fadingprediction. This long range prediction capability for fading channels would provide enabling technology for accurate power control, reliable transmitter and/or receiver diversity, more effective adaptive modulation and coding and improvements in many other components ofwireless systems. In this thesis, we demonstrate that largeimprovements in the performance are possible for both flat andfrequency-selective rapidly varying fading channels when theproposed prediction method is used. We illustrate the performanceenhancements both at the transmitter and the receiver with boththeoretical and simulation results.
