PROJECT TITLE :

Improving the probability of complete decoding of random code by trading-off computational complexity

ABSTRACT:

Random code may be a rateless erasure code that can reconstruct the original message of k symbols from any k + 10 encoded symbols with high chance of complete decoding (PCD), i.e. 99.nine% successful decoding, regardless of the message length, k. Nonetheless, random code is inefficient in reconstructing short messages. For example, a message of k = 10 symbols needs k + 10 = twenty encoded symbols, i.e. 2 times the first message length in order to attain high PCD. During this study, the authors propose micro-random code that encodes and decodes the initial message using symbols of smaller dimensions, specifically micro symbols. The authors’ analysis and numerical simulations show that micro-random code achieves high PCD with solely k + 1 encoded symbols. As the trade-off for such a gain, the quantity of steps for decoding increases exponentially with each incrementing segmentation issue, α. In addition, the numerical results show that the decoding time will increase by regarding 400p.c at α = 10, relying on the processing power of the system.