Title :
Channel Coding and Lossy Source Coding Using a Generator of Constrained Random Numbers
Author_Institution :
NTT Commun. Sci. Labs., NTT Corp., Kyoto, Japan
Abstract :
Stochastic encoders for channel coding and lossy source coding are introduced with a rate close to the fundamental limits, where the only restriction is that the channel input alphabet and the reproduction alphabet of the lossy source code are finite. Random numbers, which satisfy a condition specified by a function and its value, are used to construct stochastic encoders. The proof of the theorems is based on the hash property of an ensemble of functions, where the results are extended to general channels/sources and alternative formulas are introduced for channel capacity and the rate-distortion region. Since an ensemble of sparse matrices has a hash property, we can construct a code by using sparse matrices.
Keywords :
channel capacity; channel coding; random number generation; source coding; channel capacity; channel coding; channel input alphabet; constrained random number generator; hash property; lossy source coding; rate distortion region; reproduction alphabet; sparse matrices; stochastic encoders; Channel capacity; Channel coding; Manganese; Probability distribution; Random variables; Rate-distortion; Sparse matrices; LDPC codes; Shannon theory; channel coding; information spectrum methods; lossy source coding;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2014.2309140