Title :
Converse Coding Theorems for Identification via Channels
Author :
Oohama, Yasutada
Author_Institution :
Dept. of Commun. Eng. & Inf., Univ. of Electro-Commun., Chofu, Japan
Abstract :
In identification via channels, the sum of two types of error probabilities of identification goes to one as the block length of transmission tends to infinity at rates above capacity when channels satisfy some stochastic properties. This is well known as a strong converse theorem for the identification via channels. In this paper, we prove that the sum of two error probabilities tends to one exponentially and derive an explicit lower bound of this exponent function.
Keywords :
channel capacity; encoding; error statistics; stochastic processes; channel capacity; converse coding theorems; error probability; explicit lower bound; exponent function; identification; stochastic properties; transmission block length; Channel capacity; Decoding; Encoding; Error probability; Memoryless systems; Noise measurement; Upper bound; Exponent function; general noisy channels; identification via channels; information spectrum method; strong converse theorem;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2012.2219158