Abstract
Techniques are described herein for a switch strategy based on actor-critic reinforcement learning. This depends on not only the Received Signal Strength Indicator (RSSI) and packet loss rate but also on the distribution of error segments in a packet. The states, actions, and values for the actor-critic model may be defined to fit the switch strategy. The mechanism of dynamical adjustment may depend on the different PHY formats.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Wei, Ling; Wu, Wenjia; Li, Chuanwei; and Yu, Leo, "SWITCH STRATEGY FOR SMART UTILITY NETWORK ORTHOGONAL FREQUENCY-DIVISION MULTIPLEXING PHY BASED ON REINFORCEMENT LEARNING IN LOW-POWER AND LOSSY NETWORKS", Technical Disclosure Commons, (October 23, 2019)
https://www.tdcommons.org/dpubs_series/2593