  With the rapid growth of Internet of Things (IoT) devices, the next
generation mobile networks demand for more operating frequency bands. By
leveraging the underutilized radio spectrum, the cognitive radio (CR)
technology is considered as a promising solution for spectrum scarcity problem
of IoT applications. In parallel with the development of CR techniques,
Wireless Energy Harvesting (WEH) is considered as one of the emerging
technologies to eliminate the need of recharging or replacing the 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 (AP). More importantly, we design an
optimization framework that captures a fundamental tradeoff between energy
efficiency (EE) and spectral efficiency (SE) of the network. In particular, we
formulate a Mixed Integer Nonlinear Programming (MINLP) problem that maximizes
EE while taking into consideration of users' 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 complex heuristic algorithm, called INSTANT, 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.
