Resource Allocation For Wireless Powered Wireless Networks

With the rapid development of artificial intelligence and Internet of Things(IoT),there will be a large number of network nodes in the future wireless network,where frequent manual battery replacement is expensive and even infeasible in some specific applications.The performances of wireless communication networks are constrained by the limited battery lives of wireless devices,and the network operations maybe often interrupted by battery replacement on the devices.The use of wireless energy transfer technology can effectively overcome the inconvenience caused by the limited battery lives of wireless devices.In the wireless powered communication networks(WPCN),the remote charging of the battery of the network equipment through the wireless energy transmission technology can avoid frequent manual battery replacement,and thus can significantly improve the performance of the networks,which has been widely studied by researchers.Spectrum efficiency is an important performance metric in wireless networks.Nonorthogonal multiple access(NOMA)is a key technology for the fifth generation(5G)wireless networks to meet the heterogeneous demands on low latency,high reliability,massive connectivity,fairness,and high throughput.The key idea of NOMA is to reuse the power domain by multiple users,thereby serving multiple users in the same resource block(e.g.,time slots,subcarriers or spreading codes).Therefore,combining the WPCN with NOMA can provide the network with higher throughput,higher robustness and higher flexibility.This thesis mainly studies the resource allocation for such wireless powered wireless networks.Firstly,this thesis studies a wireless powered hybrid multiple access system that is consist of a base station and multiple users in clusters.In this system setup,to simplify the complexity of the base station's information receiver,a hybrid multiple access is adopted among the users,which are partitioned into multiple clusters.The users in the same cluster transmit in the NOMA manner,while the users among different clusters transmit in the time division multiple access manner.The working process of the network can be divided into downlink wireless energy transmission phase and uplink information transmission phase.We investigate joint phase time duration allocation and power allocation at the base station and the users in order to improve the spectrum efficiency and user fairness,respectively.Two algorithms are proposed,which maximize the system throughput and the minimum throughput of the clusters,respectively.Secondly,considering the rising energy costs,the future growth of wireless data services will also consume more energy.For an energy harvesting-based system,the energy efficiency of the system is also important to measure the performance of a wireless powered communication system.Under this situation,this thesis has expanded the research work of the previous stage.To maximize the energy efficiency of the network,we jointly optimize the time allocation between the length of wireless energy transfer from the base station to the users and the lengths of information transmission from the users to the base station,as well as the transmit power of the users.The formulated problem is non-convex and is difficult to solve.We first find the structure of the optimal solution to the problem,and then based on fractional programming technique,we propose an efficient iterative algorithm to solve the problem.In WPCN,wireless power transfer may cause high energy loss and waste due to the path loss of the channel.On the other hand,devices in the IoT can collect energy from renewable energy sources or existing radio frequency signals in addition to wireless power transfer,but these energy sources are uncertain and unstable,which may not guarantee that IoT devices can obtain enough energy to meet their communication needs.Motivated by this,this thesis assumes that the users in the WPCN can not only harvest energy from a multiple-antenna power base station,but also have the initial stored energy that come from ambient energy sources.When the user's initial energy is low and then cannot harvest enough energy from ambient energy sources,the wireless power transfer phase will be activated.The working process of the network can be divided into downlink wireless energy transmission phase and uplink information transmission phase.We investigate the activation condition of the wireless power transfer phase.Furthermore,to maximize the throughput of wireless powered communication networks,we jointly optimize the time allocation between the downlink and uplink,the energy covariance matrix of wireless power transfer at the base station and transmit power of the users.Based on the Lagrangian multiplier method,we propose an optimal algorithm to find the solution to the considered problem in closed-form.