Long range prediction and reduced feedback for mobile radio adaptive OFDM systems

Abstract

Adaptive orthogonal frequency division multiplexing (AOFDM) modulation is a promising technique for achieving high data rates required for wireless multimedia services. To accomplish efficient adaptive channel loading, the channel state information (CSI) needs to be fed back to the transmitter. Since the fading channel varies rapidly for fast vehicle speeds, long range fading prediction (LRP) is required for mobile radio AOFDM to insure reliable adaptation. We use past channel observations to predict future CST and perform adaptive bit and power allocation for the OFDM system. We derive the minimum mean-square-error (MMSE) long-range channel prediction that utilizes the time and frequency domain correlation functions of the Rayleigh fading channel. Since the channel statistics are usually unknown, robust prediction methods that do not require the knowledge of the correlation functions are developed. Statistical model of the prediction error is created and used in the design of reliable adaptive modulation. In addition, several methods that significantly reduce the feedback load for mobile radio AOFDM systems are developed and compared. We use a standard sum-of-sinusoids model and our realistic physical model to validate performance of proposed methods. Simulation results demonstrate reliable performance and robustness of the proposed techniques, thus validating feasibility of AOFDM for rapidly varying mobile radio channels