Wireless energy transfer (WET) has received considerable attention for green communications. Unbalanced energy distribution and performance outages bring difficulties to the application of WET. This paper considers a network consisting of a WET-enabled access point (AP) and several energy-harvesting and source-powered user equipments (UEs). We investigate time-frequency resource allocation of downlink (DL) and uplink (UL) wireless information transfer (WIT) and DL WET. To improve energy efficiency and resource utilization, WET and WIT are orthogonally assigned at a low-frequency narrowband and a high-frequency wideband, respectively. A practical energy harvesting model is adopted, where power conversion efficiency depends on the received power instead of being a constant. To meet UEs' different energy demands with the highest conversion efficiency, we develop beam switching, where the AP employs beamforming to charge UEs by jointly controlling power and time based on energy distributions and channel conditions. We formulate the overall energy minimization as a non-convex stochastic optimization problem, which is decomposed by fixing DL-UL time allocation ratio, transformed through Markov decision processes, and finally solved via linear programming. Simulation results verify the effectiveness of our proposed scheme on energy conservation and reveal the tradeoff of time allocation between DL and UL.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Electrical and Electronic Engineering
- Applied Mathematics