Reinforcement learning-based channel sharing in wireless vehicular networks

Abstract

In this chapter, the authors study the enhancement of the proposed IEEE 802.11p medium access control (MAC) layer for vehicular use by applying reinforcement learning (RL). The purpose of this adaptive channel access control technique is enabling more reliable, high-throughput data exchanges among moving vehicles for cooperative awareness purposes. Some technical background for vehicular networks is presented, as well as some relevant existing solutions tackling similar channel sharing problems. Finally, some new findings from combining the IEEE 802.11p MAC with RL-based adaptation and insight of the various challenges appearing when applying such mechanisms in a wireless vehicular network are presented.