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As the mobile application landscape expands, wireless networks are taskedwith supporting different connection profiles, including real-time traffic anddelay-sensitive communications. Among many ensuing engineering challenges isthe need to better understand the fundamental limits of forward errorcorrection in non-asymptotic regimes. This article characterizes theperformance of random block codes over finite-state channels and evaluatestheir queueing performance under maximum-likelihood decoding. In particular,classical results from information theory are revisited in the context ofchannels with rare transitions, and bounds on the probabilities of decodingfailure are derived for random codes. This creates an analysis framework wherechannel dependencies within and across codewords are preserved. Such resultsare subsequently integrated into a queueing problem formulation. For instance,it is shown that, for random coding on the Gilbert-Elliott channel, theperformance analysis based on upper bounds on error probability provides verygood estimates of system performance and optimum code parameters. Overall, thisstudy offers new insights about the impact of channel correlation on theperformance of delay-aware, point-to-point communication links. It alsoprovides novel guidelines on how to select code rates and block lengths forreal-time traffic over wireless communication infrastructures.

On the Performance of Short Block Codes over Finite-State Channels in the Rare-Transition Regime