Baseband Unit Aggregation Based On Deep Reinforcement Learning In Cloud Radio Access Networks

We propose a deep reinforcement learning based baseband unit aggregation policy. The proposed policy is able to guarantee users' quality of service while keeping BBU pool energy-efficient. Simulation results show that up to 80% less migration traffic can be achieved compared with benchmark heuristics with only 11% higher power consumption.