Radio resource management in energy harvesting cooperative cognitive UAV assisted IoT networks:A multi-objective approach  

作　　者：Muhammad Rashid Ramzan Muhammad Naeem Omer Chughtai Waleed Ejaz Mohammad Altaf 

机构地区：[1]Department of Electrical and Computer Engineering,COMSATS University Islamabad(CUI),Wah Campus,Pakistan [2]Department of Electrical Engineering,Lakehead University,Barrie,ON,L4M 3X9,Canada

出　　处：《Digital Communications and Networks》2024年第4期1088-1102,共15页数字通信与网络（英文版）

摘　　要：Cooperative communication through energy harvested relays in Cognitive Internet of Things(CIoT)has been envisioned as a promising solution to support massive connectivity of Cognitive Radio(CR)based IoT devices and to achieve maximal energy and spectral efficiency in upcoming wireless systems.In this work,a cooperative CIoT system is contemplated,in which a source acts as a satellite,communicating with multiple CIoT devices over numerous relays.Unmanned Aerial Vehicles(UAVs)are used as relays,which are equipped with onboard Energy Harvesting(EH)facility.We adopted a Power Splitting(PS)method for EH at relays,which are harvested from the Radio frequency(RF)signals.In conjunction with this,the Decode and Forward(DF)relaying strategy is used at UAV relays to transmit the messages from the satellite source to the CIoT devices.We developed a Multi-Objective Optimization(MOO)framework for joint optimization of source power allocation,CIoT device selection,UAV relay assignment,and PS ratio determination.We formulated three objectives:maximizing the sum rate and the number of admitted CIoT in the network and minimizing the carbon dioxide emission.The MOO formulation is a Mixed-Integer Non-Linear Programming(MINLP)problem,which is challenging to solve.To address the joint optimization problem for an epsilon optimal solution,an Outer Approximation Algorithm(OAA)is proposed with reduced complexity.The simulation results show that the proposed OAA is superior in terms of CIoT device selection and network utility maximization when compared to those obtained using the Nonlinear Optimization with Mesh Adaptive Direct-search(NOMAD)algorithm.

关 键 词：Cooperative communication Energy harvesting Power splitting Unmanned aerial vehicles Cognitive radio Internet of things Multi-objective optimization Relay assignment Power allocation 

分 类 号：V279[航空宇航科学与技术—飞行器设计] TN925[电子电信—通信与信息系统]