On the relationship between the block error and channel-state Markov models in transmissions over slow-fading channels

Block-error processes in transmissions over slow-fading channels can be accurately modeled by a two-state Markov chain [the block Markov model (BMM)]. Another line of research has focused on the use of a channel-state Markov model (CSMM) to analyze block transmissions. Although both techniques provide results that agree well with observations, the relationship between both Markov models has not been recognized in the previous literature. In this letter, we show that the BMM for slow-fading channels can be directly derived from the CSMM. In addition, we introduce a greatly simplified channel-modeling methodology. In the new methodology, the BMM is the primary channel characterization tool, and the CSMM becomes essentially an estimation technique that provides parameters for the BMM. Results of packet transmissions in slow-fading channels show that our approach provides significant improvements in both accuracy and simplicity over previously proposed techniques.