OPTIMIZING A CELLULAR NETWORK USING MACHINE LEARNING

This document describes techniques and apparatuses for optimizing a cellular network using machine learning. A network-optimization controller determines a performance metric to optimize for a cellular network. The network-optimization controller determines at least one network-configuration parameter that affects the performance metric. The network-optimization controller sends a gradient-request message to multiple base stations that directs multiple wireless transceivers to respectively evaluate gradients of the performance metric relative to the at least one network-configuration parameter. The network-optimization controller receives, from the multiple base stations, gradient-report messages generated by the multiple wireless transceivers, the gradient-report messages respectively including the gradients. The network-optimization controller analyzes the gradients using machine learning to determine at least one optimized network-configuration parameter. The network-optimization controller sends an optimization message to at least one of the multiple base stations that directs at least one of the multiple wireless transceivers to use the at least one optimized network-configuration parameter.