Resource Allocation Optimization In Unmanned Aerial Vehicle(UAV)-Assisted Radio Access Networks

With the continuous maturity of information technology and Internet-of-things(Io T)network,the communication network is moving towards an air-ground integration network,in which everything is fully and intelligently connected.Facing the communication requirements of massive nodes in intelligent air-ground integration networks,the unmanned aerial vehicle(UAV)-assisted communication techniques are emerging to provide strong support for various application scenarios.To deal with the severe air-to-ground interference,wireless backhaul design,as well as the UAVs' maneuver design,how to provide effective and efficient designs for UAV-assisted wireless access networks are the key tasks that need to be solved.As such,putting the scenarios of UAV-enabled base stations(BSs)and cellular-connected UAV users into considerations respectively,this thesis proposes efficient networking schemes and resource allocation strategies to significantly enhance the communication performance of the systems.In particular,the main research contents of this thesis are listed as follows:(1)First,for the UAV-enabled multiple access channel(MAC),on the basis of satisfying the UAV flight constraint and the communication performance balance among multiple ground users(GUs),the joint optimization method of UAV trajectory and wireless resource allocation is studied.We aim to explore the fundamental rate limits of the UAV-enabled MAC and the structural properties of the optimal UAV trajectory.In the case of non-orthogonal multiple access(NOMA)with successive interference cancellation(SIC)technique,the communication rate of GUs is maximized by jointly optimizing the UAV trajectory and the decoding order of the UAV,and then the capacity region is characterized.The optimal solution is obtained by using the Lagrangian method,and it is proved that the optimal UAV trajectory solution follows the successive-hover-fly(SHF)structure.Then,in the case of orthogonal multiple access(OMA)scenario,we jointly optimize the UAV trajectory together with time/frequency scheduling,to maximize the communication rate of GUs,and then the corresponding rate regions are characterized.Based on the proposed theoretical analysis framework,the optimal solution is obtained.It is similarly proved that the optimal UAV trajectory solution under OMA also follows the SHF structure,but with different hovering locations.Numerical results show that the proposed optimal trajectory designs achieve considerable rate gains over other benchmark schemes,and the capacity region achieved by NOMA significantly outperforms the rate regions by OMA.(2)Then,for the UAV-enabled wireless networks with multi-hop backhauls,the comprehensive design of both wireless access and backhaul links is studied.Considering the traffic flow balance constraint,power constraint,as well as the bandwidth constraint,a joint optimization scheme based on multi-UAV cooperative deployment and wireless resource allocation is proposed based on the techniques of alternating optimization and successive convex approximation(SCA).Numerical results verify that the proposed efficient design significantly improves the common throughput among all GUs as compared to other benchmark schemes.(3)Next,for the cellular-connected UAV scenario,in which the UAV user communicates with ground BSs in cellular uplink by sharing the spectrum with GUs.To tackle the severe airto-ground co-channel interference,the adaptive interference cancellation(IC)at ground BSs is investigated,in which the BSs can decode the GU's messages by adaptively switching between the mode of IC or treating interference as noise(TIN).By designing the BSs' decoding mode,jointly with the wireless resource allocation and the UAV's trajectory,we maximize the UAV's throughput,while ensuring the minimum data-rate requirements at individual GUs.As such,considering the efficient linkage and cooperation among BSs,GUs,and the UAV user,a joint optimization method of UAV trajectory design and wireless resource allocation is proposed.Under given UAV trajectory,the global optimal wireless resource allocation is derived.Under given wireless resource allocation,the iterative-based algorithm based on the SCA technique can efficiently converge to a locally optimal UAV trajectory solution.Numerical results show that the proposed design significantly improves the UAV's throughput as compared to the benchmark schemes without the adaptive IC and/or UAV trajectory optimization.(4)Furthermore,aiming at the wireless access of cellular-connected UAV in the future multi-functional network,the tradeoff between the UAV communication and the performance of the multi-functional network is studied.In particular,we consider multi-cell cooperative integrated sensing and communication(ISAC)with UAVs,in which the BS acts as a transceiver to communicate with the UAV user and estimate the location of the sensing target at the same time.As such,we jointly design the cooperative power control among BSs and UAV trajectory to minimize the energy consumption of the BSs,while satisfying the signalto-interference-noise ratio(SINR)requirements of UAV users and the Cramer-Rao lower bound(CRLB)requirement for target location estimation.Since the variables are coupled together and the SINR constraints are non-convex,thus the formulated problem is non-convex and difficult to be tackled in general.To deal with this challenge,we propose an efficient algorithm based on the alternating optimization to jointly optimize the BSs' power control as well as the UAV trajectory.In particular,the power control problem and the UAV trajectory problem are solved by using the techniques of semi-definite relaxation(SDR)and SCA,respectively.The proposed design realizes the efficient linkage between BSs and UAVs,and ensures the operation of the multi-functional network with the lowest energy consumption.This thesis innovatively investigates the UAV-assisted wireless communication systems,including UAV-enabled BSs and cellular-connected UAV users,and proposes joint optimization frameworks for cooperatively designing the UAV maneuver and the wireless resource allocation under different application scenarios,to provide efficient networking and resource allocation strategies for UAV-assisted wireless communication systems.This thesis provides basic theoretical basis for the UAV-assisted wireless access network,establishes analysis frameworks for enhancing the network performance,and provides significant guidance and reference value for the research and design of UAV communication systems.