Rateless Codes for Single-Server Streaming to Diverse Users

TL;DR

This paper explores optimized rateless coding strategies for single-server streaming to diverse users with varying demands and decoding capabilities, improving bandwidth efficiency through tailored degree distributions.

Contribution

It introduces a novel optimization framework for designing degree distributions in LT codes catering to heterogeneous user requirements and decoding methods.

Findings

Optimized degree distributions significantly reduce bandwidth consumption.

Simulation results validate the effectiveness of the asymptotic optimization for finite-length codes.

The approach outperforms traditional ideal soliton distribution and separate encoding strategies.

Abstract

We investigate the performance of rateless codes for single-server streaming to diverse users, assuming that diversity in users is present not only because they have different channel conditions, but also because they demand different amounts of information and have different decoding capabilities. The LT encoding scheme is employed. While some users accept output symbols of all degrees and decode using belief propagation, others only collect degree- 1 output symbols and run no decoding algorithm. We propose several performance measures, and optimize the performance of the rateless code used at the server through the design of the code degree distribution. Optimization problems are formulated for the asymptotic regime and solved as linear programming problems. Optimized performance shows great improvement in total bandwidth consumption over using the conventional ideal soliton distribution, or simply sending separately encoded streams to different types of user nodes. Simulation experiments confirm the usability of the optimization results obtained for the asymptotic regime as a guideline for finite-length code design.