Markov Decision-Based Pilot Optimization for 5G V2X Vehicular Communications

Abstract

This paper proposes a Markov decision process (MDP)-based pilot placement optimization approach for the radio access in 5G vehicle to everything communications to support Internet of Vehicles applications. The optimal placement problem of pilot symbols is based on a typical pilot-assisted frequency-division multiplexing transmission and simplified to a finite state-space representation. We propose and formulate a finite MDP so as to determine an appropriate pilot pattern from a set of candidate pilot configurations. Also, an enhanced pilot placement scheme is developed to reduce the complexity for solving the formulated MDP problems. Furthermore, we derive analytical expressions of the mutual information, which to some extent allow us to jointly evaluate the dynamics of the channel state in time and frequency domains. Numerical results generated by Monte Carlo simulations show that the proposed pilot optimization policy is capable of improving the channel estimation in fast time-varying vehicular channels, and the mutual information-based measurement criteria can yield more accurate evaluations in fast time-varying vehicular channels than other conventional schemes.