1 research outputs found
A Tight Estimate for Decoding Error-Probability of LT Codes Using Kovalenko's Rank Distribution
A new approach for estimating the Decoding Error-Probability (DEP) of LT
codes with dense rows is derived by using the conditional Kovalenko's rank
distribution. The estimate by the proposed approach is very close to the DEP
approximated by Gaussian Elimination, and is significantly less complex. As a
key application, we utilize the estimates for obtaining optimal LT codes with
dense rows, whose DEP is very close to the Kovalenko's Full-Rank Limit within a
desired error-bound. Experimental evidences which show the viability of the
estimates are also provided.Comment: Submitted to ISIT 2009, Seoul, Kore