Interference Control of LTE-LAA using Q-learning with HARQ

LTE-LAA (LTE-Licensed Assisted Access) is the LTE (Long Term Evolution) to use an unlicensed band. However, in addition to the currently used license band, to use the unlicensed band, interference control with Wi-Fi that also uses the unlicensed bandwidth is required. A technique called LBT (Listen Before Talk) is considered as a technique of LTE-LAA interference control. However, since the channel occupation time (TXOP) of LTE-LAA is larger than that of Wi-Fi, there is a problem that Wi-Fi channel access is hindered. As a solution to this problem, one way is to increase the chances of channel access to Wi-Fi by establishing a waiting time of T_mute in LTE-LAA to reduce TXOP of LTE-LAA and postpone transmission. In this paper we propose an interference control method for LTE-LAA using Q-learning, which is one of the reinforcement learning techniques. In the proposed method, we select TXOP and T_mute using Q-learning. In the proposed method, the number of ACKs and that of NACKs in HARQ (Hybrid Automatic Repeat Request) are used as reward. In LTE-A the user terminal generates ACK / NACK according to the received radio frame and transmits it to the BS (base station). BS retransmits according to the number of ACKs / NACKs. Learning values of TXOP, T_mute of the LTE-LAA BS can be obtained so as to increase the number of ACKs or NACKs. When the LTE-LAA BS learns to increase the number of ACKs, the throughput of LTE-LAA is controlled to be high and that of Wi-Fi is controlled to be low. On the other hand, when the LTE-LAA BS learns to increase the number of NACKs, the throughput of LTE-LAA is controlled to be low and that of Wi-Fi is controlled to be high. Simulation result shows the proposed method using LTE-LAA UE (User Equipment) and Wi-Fi UE.