Ph.D. Forum: Multi-Agent Reinforcement Learning in Wireless Network Communication
Sabrina Pochaba, Peter Dorfinger, Matthias Herlich, Roland Kwitt, Simon Hirlaender · 2024
Wireless network communication develops fast. Hence, data traffic is rising and more devices communicate like mobile users, autonomous cars and machines in factories [2]. These devices affect their communication by trying to access the same resources if they all use the full cellular spectrum. Thus, avoiding the overlap of used frequency bands and controlling the wireless network communication becomes more complicated in the future [1].