标题： 随机树代码在有限计算资源下的优化 显示英文标题

标题： The Optimization of Random Tree Codes for Limited Computational Resources

摘要： 在本文中，我们引入了在具有硬计算限制的顺序解码算法下随机树码集合的帧差错率的可达性界限，并考虑了在分支结构/轮廓和解码度量上对随机树码集合的优化。 通过数值示例，我们表明优化后的随机树码的可达性界限可以接近纯随机码的最大似然（ML）解码性能。 显示英文摘要

摘要： In this paper, we introduce an achievability bound on the frame error rate of random tree code ensembles under a sequential decoding algorithm with a hard computational limit and consider the optimization of the random tree code ensembles over their branching structures/profiles and the decoding measure. Through numerical examples, we show that the achievability bound for the optimizated random tree codes can approach the maximum likelihood (ML) decoding performance of pure random codes.