Energy Efficient Resource Allocation in EH-Enabled CR Networks for IoT

Cognitive radio (CR) can be leveraged to mitigate the spectrum scarcity problem of Internet of Things (IoT) applications while wireless energy harvesting (WEH) can help reduce recharging/replacing batteries for IoT and CR networks. To this end, we propose to utilize WEH for CR networks in which the CR devices are not only capable of sensing the available radio frequencies in a collaborative manner but also harvesting the wireless energy transferred by an access point. More importantly, we design an optimization framework that captures a fundamental tradeoff between energy efficiency (EE) and spectral efficiency of the network. In particular, we formulate a mixed integer nonlinear programming problem that maximizes EE while taking into consideration of user buffer occupancy, data rate fairness, energy causality constraints, and interference constraints. We further prove that the proposed optimization framework is an NP-hard problem. Thus, we propose a low complexity heuristic algorithm, to solve the resource allocation and energy harvesting optimization problem. The proposed algorithm is shown to be capable of achieving near optimal solution with high accuracy while having polynomial complexity. The efficiency of our proposal is validated through well designed simulations.