Multi-Dimensional Resource Allocation for Uplink Throughput Maximisation in Integrated Data and Energy Communication Networks

The interdisciplinary research of the radio-frequency (RF) signal-based wireless power and information transfer is expected to address the energy shortage issue in the massively deployed low-power Internet of Things devices. Different from conventional wireless powered communication networks (WPCNs), the hybrid base station (H-BS) adopts the simultaneous wireless information and power transfer (SWIPT) for the sake of satisfying the downlink data and energy requests of the multiple user equipments (UEs). The energy harvested from the downlink transmissions can be depleted for supporting the UEs' uplink transmissions. Integrating SWIPT in the downlink transmission of the WPCN yields a generic integrated data and energy communication network, where the H-BS is equipped with multiple antennas and both the downlink and uplink transmissions are slotted in the time-domain. Furthermore, both the sum-throughput and the fair-throughput of the uplink transmissions are maximized by jointly optimizing the transmit beamformer of the H-BS in the spatial-domain, the time-slot allocation in the time-domain and the signal splitting strategies of the UEs in the power domain, while satisfying the UEs' minimum downlink transmission requirements. Due to the non-convexity of the problem, a low-complexity successive convex approximation-based algorithm is relied upon for obtaining the optimal resource allocation scheme in the time-domain, power-domain, and spatial-domain. The numerical results validate the efficiency of our proposed resource allocation algorithm and they also demonstrate that supporting low-rate data services during the downlink transmissions does not degrade the wireless power transfer and hence does not reduce the uplink throughput.