LTE-U and Wi-Fi Coexistence Algorithm Based on Q-Learning in Multi-Channel

Abstract

Due to the lack of resources in the low spectrum, long term evolution (LTE) in unlicensed spectrum (LTE-U) technology has been proposed to extend LTE to unlicensed spectrum. LTE-U undertakes the task of streaming data traffic for licensed spectrum, which can greatly enhance the capacity of the system. However, the introduction of LTE-U technology also gives rise to the problem of coexistence with Wi-Fi systems. In this paper, an LTE-U and Wi-Fi coexistence algorithm is proposed in multi-channel scenarios based on Q-learning. By taking the idea of alternately transferring data in LTE-U and Wi-Fi, the algorithm takes into account both the fairness and the performance of the system and optimizes the duty cycle. The simulation results show that the proposed algorithm can effectively improve the throughput of the system in the premise of ensuring fairness.

Keywords

• Long term evolution (LTE)-U
• Wi-Fi
• Q-Learning
• reinforcement learning
• coexistence algorithm