End-to-end intelligent MCS selection algorithm
Xiaosong Xue, Wei Pan, Fang Yan, Na Li · 2024
In this paper, an end-to-end intelligent modulation and coding scheme (MCS) algorithm is proposed, where the reinforcement learning (RL) is exploited. The proposed algorithm takes channel information and measurements as the input, and intelligently selects the proper MCS value to obtain the maximum throughput. The proposed is end-to-end and the simulation results show the better performance of the proposed algorithm. Average MCS values and corresponding throughput are respectively improved by 2.1% and 2%.