The Novel Technique For UAV-assisted Wireless Communication Systems

UAV(unmanned aerial vehicle)has numerous unique properties including high mobility,flexible deployment,low-cost,and line-of-sight(Lo S)dominant UAV-ground channels,which make it becoming as one of the key technologies to realize sky network in the future.However,the UAV integrated in the current cellular-connected network faces new problems and challenges,such as the short time for flight,the aggregation of co-channel interference,and more easier to be wiretaped for the UAV-ground link,etc.This dissertation focuses on the novel technique for UAV-assisted wireless communication systems,and studies the UAV's limited on-board battery capacity issue,the co-channel interference for multi-UAV cooperation issue,and secure transmission for multi-UAV cooperation issue.In addition,to tackle the computation issue for the resource-limited and energy-limited ground terminals and the passive information transmission of intelligent reflecting surface(IRS),we propose to leverage a UAV to help them.The main contributions are listed as follows:1.Due to the limited on-board battery capacity on UAV,we propose a power-efficient UAVassisted wireless sensor network(WSN)by jointly optimizing the 2D UAV trajectory and communication transmission.Specifically,the UAV is used as a flying base station to communicate with the numerous sensor nodes(SNs)on the ground with a flexible movement path.We aim at minimizing the total power consumption of the UAV with a guarantee of the required transmission rate of SNs by jointly optimizing the SN-UAV scheduling scheme,power allocation strategy and flight trajectory of the UAV.To address this nonconvex and mixed-integer optimization problem,the block coordinate descent(BCD)method is proposed to decompose the original problem into two sub-problems.We then solve each sub-problem by using successive convex approximation(SCA)techniques,and then alternately optimize each sub-problem until the algorithm converges.Numerical results show a significant performance gain of our proposed scheme is achieved compared with the other benchmarks.2.In order to address the co-channel interference issues among multiple UAV cooperative systems,we consider to maximize the system throughput by jointly optimizing the 3D UAV trajectory and resource allocation.Specifically,for the downlink transmission network,where one UAV acting as a disseminator,referred to as UAV-AP,is connected to multiple access points(AP);For the uplink transmission network,the other UAV acting as a base station(BS),referred to as UAV-BS,collects data from numerous sensor nodes(SNs).We first consider a special case where the UAV-BS and UAV-AP trajectories are pre-determined,and we aim at maximizing the system throughput by jointly optimizing communication scheduling,and UAV-AP/SN transmit power.Although the resulting problem is an integer and non-convex optimization problem,a globally optimal solution is obtained by applying the polyblock outer approximation(POA)method based on the problem's hidden monotonic structure.Subsequently,for the general case by considering the additional 3D UAV trajectory optimization,which makes the problem more difficult to handle compared with the case that the UAV trajectory is pre-determined.To tackle such complicated problem,we first divide the original problem into several sub-problems,and leverage the SCA method to solve each sub-problems,then alternately optimize each sub-problem until the algorithm converges.Numerical results demonstrate that the proposed design is able to achieve significant system throughput gain over the benchmarks.In addition,the SCA-based method can achieve nearly the same performance as the POAbased method,but with much lower computational complexity.3.To realize a multi-UAV enabled cooperative secure transmission scheme in the presence of multiple potential eavesdroppers,we propose to leverage multiple jamming UAVs(JUAVs)cooperatively transmit interference signals to multiple eavesdroppers in order to help multiple source UAVs(SUAVs)secure transmission.Specifically,JUAVs transmit the interference signals to the ground eavesdroppers so that prevent eavesdroppers' wiretap from the SUAVs.By taking into account the limited energy budget of UAVs,and strike a balance between maximizing the system secrecy and minimizing the UAV's energy consumption,our goal is to maximize the system secrecy energy efficiency(SEE)by jointly optimizing the UAV trajectory,transmit power and user scheduling.The resulting optimization problem is shown to be a non-convex and mixed-integer fractional optimization problem,which is challenging to solve.To tackle this problem,we first transform the fractional problem into a subtraction form by using Dinkelbach method,and decompose the original problem into three sub-problems,and then an efficient iterative algorithm is proposed by leveraging the BCD and SCA techniques until the algorithm converges.Simulation results show that our proposed JUAV-aided secrecy rate maximization scheme achieves significantly higher secrecy rate compared with no JUAV-aided secure scheme.In addition,the SEE is firstly increasing with period time and then decreasing with period time.Morevoer,the schemes based on UAV trajectory optimization outperform the other benchmarks without UAV trajectory optimization.4.In order to address the resource-limited and energy-limited of ground terminals,we propose a power-efficient UAV-assisted mobile computing system.To tackle the huge volume of data at ground terminals,we propose a novel resource partitioning strategy scheme,where one portion of bits at ground terminals is computed locally and the remaining portion is transmitted to UAV for computing.Our goal is to minimize the total energy consumption of ground terminals by jointly optimizing bit allocation,resource partitioning,power allocation at terminals/UAV,terminals-UAV scheduling and UAV trajectory.We consider two scenarios,one is the ideal case where the UAV is not constrained by battery capacity and computational resource,and the UAV's trajectory constraint is only related to the maximum UAV speed.The other one is the practical case where the UAV is constrained by the energy budget as well as computational resource,and the UAV is not only related to the maximum speed,but also the maximum acceleration.To address such two integer and non-convex problems,we decompose the problems into two sub-problems.Specifically,in the first sub-problem,the communication scheduling is obtained by solving dual problem with given UAV trajectory.In the second sub-problem,the UAV trajectory is obtained by using SCA techniques with given bit allocation,resource partitioning,power allocation at terminals/UAV,terminals-UAV scheduling.Then,an iterative algorithm is proposed to optimize each sub-problem until the algorithm converges.Numerical results are provided to demonstrate the superiority of our proposed scheme over the benchmarks.5.To realize the intelligent reflecting surface(IRS)passive information transmission,we propose a symbiotic UAV-enhanced IRS radio system.Specifically,on the one hand,there are multiple IRS available to sense environmental information,then the IRS sends its own data to the BS by controlling its on/off state.On the other hand,the IRS is able to change the amplitude and/or phase of the incident signal,thereby enhancing the UAV communication performance.We first consider the problem of maximizing the minimum of achievable rate among IRSs by jointly optimizing the UAV trajectory,IRS phase shift matrix,and IRS scheduling.To address this problem,a commonly used method is based on the relaxation-based method.Specifically,we first relax the binary scheduling value into a continuous scheduling value in the interval [0,1],and solve the relaxed problem,then reconstruct the scheduling value into a binary scheduling value.However,this conventional relaxation-based methods cannot solve such mixed integer non-convex problem since the minimum primary rate requirements may not be satisfied by the binary reconstruction operation.To address this issue,we first transform the binary constraints into an equivalent series of equality constraints,and add the penalty terms into the objective function.Then,a penalty-based algorithm is proposed to obtain a high-quality suboptimal solution.Second,we consider the weighted sum-rate(WSR)maximization problem among all IRS.Although the proposed penalty-based algorithm can also be applied to this problem,it incurs high computational complexity.To reduce its complexity,we first relax the binary variables into continuous variables,and then propose an alternating optimization(AO)method to solve it.We prove that the obtained scheduling results are the same as the binary results from the AO method,which indicates that the primary rate requirements are always satisfied.Simulation results showed that the adjustment of IRS phase has significant impact on the system performance.Moreover,the UAV trajectory optimization can substantially improve the IRS transmission rate,which demonstrates the effectiveness of our proposed scheme.