employed various mathematical models to study energy storage mechanisms for EH systems. Among these models, queueing-theoretic energy quantization models [@tadayon2013power] are arguably the most common and well-established ones. These models can reflect the practical characteristics of energy storage systems relatively accurately, and are generally amenable to mathematical analysis when invoked in communication systems. Concurrently, understanding the energy consumption profile of wireless devices is also essential, as the energy retrieval rate from a storage unit may affect the lifetime of a device. However, while it was relatively easy to model and estimate the energy consumption behavior of a communication device in the past because mostly the circuit, baseband, radio frequency and power amplifier components consumed the energy, nowadays it is much more difficult to accurately understand and model the energy needs of communication devices due to the ever-increasing complexity of modern devices and applications [@rice2010measuring]. Therefore, along with the introduction of EH wireless communication technology, which relies on environment-friendly techniques to generate energy from renewable resources, the effective use of the generated energy to guarantee energy availability when required, led to a paradigm shift in research on radio resource allocation [@ahmed2015survey]. Particularly, in addition to spectral efficiency and quality-of-service (QoS) constraints, 