  Energy saving in wireless networks is growing in importance due to increasing
demand for evolving new-gen cellular networks, environmental and regulatory
concerns, and potential energy crises arising from geopolitical tensions. In
this work, we propose an approximate dynamic programming (ADP)-based method
coupled with online optimization to switch on/off the cells of base stations to
reduce network power consumption while maintaining adequate Quality of Service
(QoS) metrics. We use a multilayer perceptron (MLP) given each state-action
pair to predict the power consumption to approximate the value function in ADP
for selecting the action with optimal expected power saved. To save the largest
possible power consumption without deteriorating QoS, we include another MLP to
predict QoS and a long short-term memory (LSTM) for predicting handovers,
incorporated into an online optimization algorithm producing an adaptive QoS
threshold for filtering cell switching actions based on the overall QoS
history. The performance of the method is evaluated using a practical network
simulator with various real-world scenarios with dynamic traffic patterns.
