Joint source-channel coding error exponent for discrete communication systems with Markovian memory
We study the error exponent, E-J, for reliably transmitting a discrete stationary ergodic Markov (SEM) source Q over a discrete channel W with additive SEM noise via a joint source-channel (JSC) code. We first establish an upper bound for E-J in terms of the Renyi entropy rates of the source and noise processes. We next investigate the analytical computation of E-J by comparing our bound with Gallager's lower bound (1968) when the latter one is specialized to the SEM source-channel system. We also note that both bounds can be represented in Csiszar's form (1980), as the minimum of the sum of the source and channel error exponents. Our results provide us with the tools to systematically compare E-J with the tandem (separate) coding exponent E-T. We show that as in the case of memoryless source-channel pairs E-J   E-T. Numerical results indicate that E-J approximate to 2E(T) for many SEM source-channel pairs, hence illustrating a substantial advantage of JSC coding over tandem coding for systems with Markovian memory.
error exponent joint source-channel (jsc) coding renyi entropy rate additive noise error probability markov types stationary ergodic markov source-channel tandem separate coding