  The Fourth Industrial Revolution (Industrial 4.0) is coming, and this
revolution will fundamentally enhance the way the factories manufacture
products. The conventional wired lines connecting central controller to robots
or actuators will be replaced by wireless communication networks due to its low
cost of maintenance and high deployment flexibility. However, some critical
industrial applications require ultra-high reliability and low latency
communication (URLLC). In this paper, we advocate the adoption of massive
multiple-input multiple output (MIMO) to support the wireless transmission for
industrial applications as it can provide deterministic communications similar
as wired lines thanks to its channel hardening effects. To reduce the latency,
the channel blocklength for packet transmission is finite, and suffers from
transmission rate degradation and decoding error probability. Thus,
conventional resource allocation for massive MIMO transmission based on Shannon
capacity assuming the infinite channel blocklength is no longer optimal. We
first derive the closed-form expression of lower bound (LB) of achievable
uplink data rate for massive MIMO system with imperfect channel state
information (CSI) for both maximum-ratio combining (MRC) and zero-forcing (ZF)
receivers. Then, we propose novel low-complexity algorithms to solve the
achievable data rate maximization problems by jointly optimizing the pilot and
payload transmission power for both MRC and ZF. Simulation results confirm the
rapid convergence speed and performance advantage over the existing benchmark
algorithms.
