Computer Science – Information Theory
Scientific paper
2009-01-13
Computer Science
Information Theory
Submitted to ISIT 2009, Seoul, Korea
Scientific paper
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.
Kim Beom-Jin
Lee Ki-Moon
Radha Hayder
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