A Deterministic Scheduling Policy for Low-Latency Wireless Communication With Continuous Channel States

Abstract

Low-latency and energy-efficient wireless communication holds the potential of enabling the industrial internet of things (IIoT), automatic driving, and telesurgery. Cross-layer scheduling, which is aware of both the channel and queue states, has attracted considerable attention recently because it is capable of reducing the average delay substantially while meeting a given average power constraint. As a result, there has been considerable work, in which joint channel and buffer aware scheduling is formulated as a constrained Markov decision process (CMDP). In general, the optimal solution to a CMDP problem is characterized by the stationary probability of actions, yielding probabilistic cross-layer scheduling with possibly high complexity in practice. In this paper, we are interested in the low-latency and energy-efficient stationary cross-layer scheduling policy for wireless channels with continuous channel states, e.g. Rayleigh fading. It is interestingly shown that a deterministic cross-layer scheduling policy can achieve the optimal tradeoff between the average delay and power. In other words, the signaling complexity of cross-layer scheduling can be significantly reduced without causing sub-optimality. Simulation results also demonstrate that our work provides a low-complexity solution for low-latency and energy-efficient wireless communications.