Novel Channel Quality Indicator Prediction Scheme for Adaptive Modulation and Coding in High Mobility Environments

In this paper, a novel channel quality indicator (CQI) prediction scheme for adaptive modulation and coding in high-speed mobility environments is proposed, where the wavenumber spectrum segmentation filters' bank is utilized to improve the estimation accuracy of channel prediction algorithm by enhancing the correlation of wireless channels in each orthogonal subspace. In the proposed method, the channel estimation, channel prediction, and signal-to-noise-rate (SNR) prediction are processed on the orthogonal subspace level, which can significantly decrease the mismatch level of the feedback CQI under the fast time-varying channels. Based on the predicted SNR after subspace signal combination, the effective SNR is obtained and is utilized to calculate the feedback CQI parameter. The autocorrelation function and spatial fading rate are analyzed with different feedback delays, which show that our proposed scheme provides stronger correlation of channels with the order of wavenumber spectrum segmentation filters' bank increasing. The simulation results show that the proposed scheme can achieve better throughput performance even with larger feedback delay in high-speed mobility environments.