Optimizing Sleep-Wake-Transmit Scheduling to Minimize Age of Information in Wireless-Powered Communication Networks

With the advancement of Industry 4.0, IoT devices in real-time control systems demand high information freshness, making the Age of Information (AoI) a critical performance metric. In wireless-powered communication networks (WPCNs), sensor nodes harvest energy from radio frequency signals, but the randomness of energy harvesting and sleep-wake scheduling challenges hinder AoI optimization-premature/ delayed wake-ups and the transmission power-rate trade-off further complicate balancing energy efficiency and information freshness. To minimize the long-term average AoI under power constraints, this paper proposes an Optimizing Sleep-Wake-Transmit Scheduling (OSS) strategy, which jointly optimizes the wake-up energy threshold, transmission rate, and transmission energy threshold. Dynamically adapting to energy variability and network conditions, OSS outperforms conventional methods, and simulation results validate its effectiveness in reducing the long-term average AoI.