Applications of Deep Learning Algorithms for RFEH, WPT and SWIPT Systems: A Review

Deep learning (DL) has gained vast popularity in the research community in the recent years. The implementation of various DL algorithms in Radio-frequency energy harvesting (RFEH), Wireless power transmission (WPT), and Simultaneous wireless information and power transfer (SWIPT), among other numerous electromagnetics applications, has been widely explored to minimize the design complexity. This review article highlights recent developments in DL applied to RFEH, WPT, and SWIPT systems. It aims to provide interested readers and practitioners with helpful insights on the efficacy and potentials of DL algorithms as computational tools.