State Estimation Entropy for Two-State Markov Sources in Slotted ALOHA Random Access Channels

We study a system in which terminals monitoring two-state Markov sources communicate towards a common receiver over a slotted ALOHA random access channel. We analyze the system performance in terms of state estimation entropy (SEE), which measures the uncertainty at the receiver about the sources’ state. Two channel access strategies are studied, one that is influenced by the source behaviour and one that is independent of it. By means of density evolution analysis, we show that the former can yield a remarkable reduction of the SEE.