The asymptotic performance of systematic rateless codes is first analysed using Gaussian approximation (GA) based on mutual information, which provides more accurate decoding thresholds than the method based on message mean. A modified linear program (LP) algorithm is proposed, where two key parameters are precomputed to efficiently search degree distributions with low overhead and appropriate average degree. The asymptotic analysis and simulation results show that the optimized code outperforms the codes obtained by conventional LP. Furthermore, the effects of outer code on overall code rate and decoding complexity are discussed.

中文翻译：

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一种有效的系统无速率代码设计

首先使用基于互信息的高斯近似（GA）分析系统无速率码的渐近性能，这比基于消息均值的方法提供了更准确的解码阈值。提出了一种改进的线性规划算法，其中预先计算了两个关键参数以有效地搜索具有低开销和适当平均度的度分布。渐近分析和仿真结果表明，优化后的代码性能优于传统的LP算法。此外，讨论了外码对整体码率和解码复杂度的影响。