Minimized Variance Control of Communication Delays for Markov Switching Channels in IIoT.

This paper mainly considers the wireless communication scenario where equipment in different working conditions switches its channel state in the actual industrial field. To address the problem of uncertain communication delays in wireless control systems, we model the randomness introduced by the inevitable multipath fading channels as a Markov process. The distribution of communication delays is controlled in a statistical sense, given the probability density function(PDF) of power gain under various channel states and the Markov transition matrix. Based on the principle of Shannon channel capacity, we propose an algorithm for controlling the shape of the PDF to find the optimal transmission power for each channel state in the sense of minimizing delay variance. Then the transmission power is adjusted according to the channel state in real-time, and the PDF shape of the communication delays is controlled to present a Gaussian distribution of minimized variance. Compared with the delay variance of 80 ms by using fixed transmission power, the simulation results show that the variance of the communication delays is reduced to 0.1 ms when the wireless channel states is known.