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

Long-term scheduling and power control for wirelessly powered cell-free IoT