A Joint Wireless Data-Power Exchange Approach for Distributed Energy Harvesting Networks

This work addresses the problem of efficient joint wireless data-energy transfer in distributed networks. We consider devices capable of exchanging data and energy wirelessly, aiming at optimal data/energy transfer scheduling. Wireless Power Transfer resembles energy-harvesting but it bears its own peculiarities. We formulate mathematically the evolution of the data queue and battery state of each node according to a back-pressure inspired approach, and define an optimization problem aiming at better energy balancing. We employ a dual Lagrange multiplier solution, and through simulation and analysis, we identify the critical parameters determining the behavior of the system. This is a cornerstone work towards developing a more generic framework within the conceived 6G architecture, and here we demonstrate its theoretical and practical potentials.