  We propose a coordinated random access scheme for industrial
internet-of-things (IIoT) scenarios, with machine-type devices (MTDs)
generating sporadic correlated traffic. This occurs, e.g., when external events
trigger data generation at multiple MTDs simultaneously. Time is divided into
frames, each split into slots and each MTD randomly selects one slot for
(re)transmission, with probability density functions (PDFs) specific of both
the MTD and the number of the current retransmission. PDFs are locally
optimized to minimize the probability of packet collision. The optimization
problem is modeled as a repeated Markov game with incomplete information, and
the linear reward-inaction algorithm is used at each MTD, which provably
converges to a deterministic (suboptimal) slot assignment. We compare our
solution with both the slotted ALOHA and the min-max pairwise correlation
random access schemes, showing that our approach achieves a higher network
throughput with moderate traffic intensity.
