End-to-end Throughput Maximization for Underlay Multi-hop Cognitive Radio Networks with RF Energy Harvesting

摘要

This paper studies a green paradigm for the underlay coexistence of primaryusers (PUs) and secondary users (SUs) in energy harvesting cognitive radionetworks (EH-CRNs), wherein battery-free SUs capture both the spectrum and theenergy of PUs to enhance spectrum efficiency and green energy utilization. Tolower the transmit powers of SUs, we employ multi-hop transmission with timedivision multiple access, by which SUs first harvest energy from the RF signalsof PUs and then transmit data in the allocated time concurrently with PUs, allin the licensed spectrum. In this way, the available transmit energy of each SUmainly depends on the harvested energy before the turn to transmit, namelyenergy causality. Meanwhile, the transmit powers of SUs must be strictlycontrolled to protect PUs from harmful interference. Thus, subject to theenergy causality constraint and the interference power constraint, we study theend-to-end throughput maximization problem for optimal time and powerallocation. To solve this nonconvex problem, we first equivalently transform itinto a convex optimization problem and then propose the joint optimal time andpower allocation (JOTPA) algorithm that iteratively solves a series offeasibility problems until convergence. Extensive simulations evaluate theperformance of EH-CRNs with JOTPA in three typical deployment scenarios andvalidate the superiority of JOTPA by making comparisons with two other resourceallocation algorithms.