Long-Term Scheduling and Power Control for Wirelessly Powered Cell-Free IoT

We investigate the long-term scheduling and power control scheme for a wirelessly powered cell-free Internet-of-Things (IoT) network which consists of distributed access points (APs) large number sensors. In each time slot, subset sensors is scheduled uplink data transmission or downlink transfer. Through asymptotic analysis, we obtain closed-form expressions harvested energy achievable rates that are independent random pilots. Then, using these expressions, formulate problem to maximize minimum time-average rate among all while maintaining battery state sensor higher than predefined level. Using Lyapunov optimization, mode, active set, coefficients slot jointly determined. Finally, simulation results validate accuracy our derived reveal boosted significantly by proposed compared with simple greedy scheme.