Fine-Granularity Loading Schemes Using Adaptive Reed-Solomon Coding for xDSL-DMT Systems

While most existing loading algorithms for xDSL-DMT systems strive for the optimal energy distribution to maximize their rate, the amounts of bits loaded to subcarriers are constrained to be integers and the associated granularity losses can represent a significant percentage of the achievable data rate, especially in the presence of the peak-power constraint. To recover these losses, we propose a fine-granularity loading scheme using joint optimization of adaptive modulation and flexible coding parameters based on programmable Reed-Solomon (RS) codes and bit-error probability criterion. Illustrative examples of applications to VDSL-DMT systems indicate that the proposed scheme can offer a rate increase of about in most cases as compared to various existing integer-bit-loading algorithms. This improvement is in good agreement with the theoretical estimates developed to quantify the granularity loss.