Performance of adaptive coded modulation enabled by long-range fading prediction with data-aided noise reduction

Abstract

Performance of uncoded adaptive modulation (UAM) and adaptive coded modulation (ACM) enabled by the long-range prediction (LRP) that utilizes data-aided noise reduction (DANR) is investigated for rapidly varying mobile radio channels. Due to improved prediction accuracy and low pilot rate, the DANR-aided LRP outperforms previously proposed prediction methods that rely on oversampled pilots to achieve noise reduction (NR). While ACM is more sensitive to prediction errors than UAM, utilization of DANR substantially increases its spectral efficiency (SE) relative to previously proposed methods. The set of SNR values and prediction ranges where positive coding gain is achieved by ACM enabled by DANR-aided LRP is determined. It is also demonstrated that adaptive modulation (AM) aided by LRP has better performance for the realistic physical model than for the Jakes model in the practical SNR range.