An Intelligent Approach to Spectrum Sharing Process for Coexistence Between Cellular and Wi-Fi Technologies

It is anticipated that New-Radio Unlicensed (NR-U) technology will offload its traffic to unlicensed spectrum, such as the 5 GHz band. Nevertheless, NR-U transmissions must coexist with the current Wi-Fi networks in the 5 GHz band. The majority of current coexistence plans take into account coordinated Wi-Fi and NR-U networks, where a centralized coordinator communicates the traffic demands of the co-located networks. However, using this technique to estimate Wi-Fi traffic increases the complexity, traffic overhead, and response times. Furthermore, the conventional Listen-Before- Talk (LBT) process of NR-U is unable to ensure enough fairness of the system. Therefore, an efficient coexistence mechanism must be required to improve the fairness. For this purpose, this paper presents an intelligent LBT based coexistence mechanism to maintain the fairness using Q-learning. In this proposed scheme, the NR-U base station optimizes its maximum channel occupancy time with respect to Wi-Fi access points, based on Q-learning algorithm to improve the system performance. We also make a performance comparison between the proposed and traditional LBT mechanisms. The simulation results show that our proposed mechanism provides better fairness compared to the conventional LBT mechanisms.