Combining Long-Short Term Memory and Reinforcement Learning for Improved Autonomous Network Operation

A combined LSTM and RL approach is proposed for dynamic connection capacity allocation. The LSTM predictor anticipates periodical long-term sharp traffic changes and extends short-term RL knowledge. Numerical results show remarkable performance.