Energy-Efficient Resource Allocation in Cognitive Wireless-Powered Hybrid Active-Passive Communications

Abstract

Integrating hybrid active-passive communications into cognitive radio can achieve a spectrum- and energy-efficiency information transmission, while the resource allocation has not been well studied particularly for the network with multiple secondary users (also termed as the Internet of Things (IoT) users). In this article, we formulate an optimization problem to maximize the energy efficiency of all the IoT nodes in a cognitive wireless-powered hybrid active-passive communication network by taking the interference from the IoT node to the primary link, the energy causality constraint, and the minimum throughput constraint per IoT node. By using the Dinkelbach method and introducing auxiliary variables, we devise an iterative algorithm to optimally solve the formulated problem. Computer simulations are provided to validate the quick convergence of the iterative algorithm and the advantages of the proposed scheme in terms of the energy efficiency.