Q-learning based Handover Algorithm for High-Speed Rail Wireless Communications

High-speed railways (HSRs) has become one of the most preferable modes of transportation. In the evolution of the railway wireless communication system from Long Term Evolution for Railway (LTE-R) to the 5th Generation Wireless System (5G), the rapid increase in the train speed and number of base stations along the railway track led to challenging handover (HO) problems, such as high failure rate and frequent HOs. In order to address this challenge, an improved handover decision strategy is proposed based on Q-learning algorithm. The simulation results demonstrate that our proposed scheme is capable of reducing the number of unnecessary handover and improving the network performance remarkably.