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Internet of Things (IoT) networks have gained significant attention in recent years as it has the potential to transform various industries. A key concern, however, is that sensing devices have limited operational lifetime. Specifically, they have finite energy, which affects the amount of data they are able to collect and upload. One solution is to power these devices wirelessly, where devices harvest energy from Radio Frequency (RF) signals from transmitters such as a Hybrid Access Point (HAP). A key issue, however, is that energy delivery and data transmissions may be conducted on the same frequency band. This means a HAP has to determine a transmission schedule for energy or/and data transmissions. Another issue is that the channel gain of devices varies over time, which affects the amount of harvested energy and transmitted data. In this respect, a challenging issue is that an HAP has causal channel state information only, meaning it is not aware of energy arrivals or channel gain ....

Integer Linear Program , Radio Frequency , Hybrid Access Point , Mixed Integer Linear Program , Rate Splitting Multiple Access , Markov Decision Process , Machine Learning , Channel Access , F Charging ,