Cross-layer transmission and energy scheduling under full-duplex energy harvesting wireless OFDM joint transmission

Abstract

This paper studies the design of the optimal and online cross-layer transmission and energy schedulings for a full-duplex energy harvesting wireless orthogonal frequency division multiplexing (OFDM) joint transmissions. Supported by today’s power management integrated circuit, the full-duplex energy harvesting system becomes a reality, which can overcome the transmission time loss problem caused by the half-duplex constraint of the energy storage unit (ESU) in the serial Harvest-Store-Use system. However, its corresponding modeling is still unexplored. Therefore, the full-duplex energy harvesting system is first modeled and proved to be equivalent to a composition of energy behavior models of Harvest-Store-Use in fine-time granularity. Then, the convex optimization problem of cross-layer transmission and energy scheduling is formulated with the objective to maximize the sum of transmission throughput during successively multiple time units, which takes into account the temporal variance of energy harvesting rates and channel states, and the limited capacity of ESUs. The optimal power allocation with three dimensions of time, channel and antenna is solved by utilizing the dual decomposition method with the pre-known temporal variance, and the corresponding result of the system throughput provides the theoretical upper bound. Finally, to reduce the throughput degradation caused by channel state prediction errors, a non-convex online scheduling problem is formulated as the classical energy efficiency format. It is transformed into a convex optimization problem by exploiting the properties of fractional programming, and then, an efficiently iterative solution is designed. Numerical results show that the average throughput of the online algorithm is 24% greater than that of existing time-energy adaptive water-filling algorithm. The degradation of the average throughput is less than 19% with probability 90%, even as the channel prediction error reaches 20%. These results provide guidelines for the design and optimization for full-duplex energy harvesting joint transmission systems.