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The Progressive Edge Growth (PEG) algorithm is one of the most widely-usedmethod for constructing finite length LDPC codes. In this paper we consider thePEG algorithm together with a scheduling distribution, which specifies theorder in which edges are established in the graph. The goal is to find ascheduling distribution that yields "the best" performance in terms of decodingoverhead, performance metric specific to erasure codes and widely used forupper-layer forward error correction (UL-FEC). We rigorously formulate thisoptimization problem, and we show that it can be addressed by using geneticoptimization algorithms. We also exhibit PEG codes with optimized schedulingdistribution, whose decoding overhead is less than half of the decodingoverhead of their classical-PEG counterparts.

Scheduled-PEG construction of LDPC codes for Upper-Layer FEC