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For the Energy harvesting (EH) transmitter equipped with a Reliable Energy Backup (REB), the following problem is challenging and important: how to minimize the amount of energy supplied by the REB, such that the harvested energy is efficiently utilized for transmitting a given amount of data within a fixed delay constraint. In this paper, we first develop a stochastic model for this problem. We then discuss the optimization issue of delay-constrained data transmission over a fading wireless channel. We transform the delay constraint into the penalty function, and then the energy constrained control problem is modeled as a Markov decision process (MDP) without constraint, by which we obtain the optimal energy supplementary policy and the minimum of the expected energy consumption from REB. In the special case that the energy of the transmitter is supplied by REB alone, we find that the optimal energy supplementary policy is non-decreasing in the elapsed transmission time and for the remaining task of data transmission. This substantially reduces the computational complexity required to implement the optimal energy supplementary policy for a general EH wireless device. Numerical studies validate the theoretical findings, and observations are outlined to demonstrate the characteristics of the optimal energy supplementary policy and the minimum expected energy expenditure from the REB.

Summary Energy harvesting wireless communication system (EH‐WCS) has the capability of harvesting energy for system operations from the surrounding renewable energy sources. However, the randomness and instability of the harvested energy will result in the depletion of the energy consumption. To provide reliable communication services with the quality of service (QoS) guarantee, it is necessary for the EH‐WCS to use a reliable energy backup (REB) for supplying energy to the system during the failure of its primary energy source. In this paper, a novel stochastic model, i.e., the extended Markov fluid flow model, is proposed to describe the EH‐WCS with REB. The Kolmogorov forward equations of the system model are derived. By solving the corresponding equations, we obtain the stationary distributions of the key performance metrics for the EH‐WCS with REB, including the average energy consumption rate of the EH‐WCS, the residual energy distribution, the average energy supply rate by REB, the packet queue length in data buffer, the data queue delay, and the packet blocking probability. A numerical example is provided to investigate the theoretical results, and the effects of the system parameters on the performance are further studied numerically. Both the theoretical insights and the numerical analyses are believed to be important for the design of EH‐WCSs.

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