Research On Physical Layer Secure Communications Technology For UAV-assisted Edge Offloading Computing

The development of mobile communication technology has brought about explosive data growth and high-speed traffic flow,giving rise to various latency-sensitive,computation-intensive and other emerging services.In order to provide edge computing services to users flexibly and reduce the load on core networks,unmanned aerial vehicle(UAV)-assisted mobile edge computing(MEC)platform is proposed to make up for the shortage of terrestrial cellular network communications.However,due to the broadcast characteristics of wireless communication channels and the limited battery capacity of UAVs,how to improve the security and confidentiality of the offloading process and reduce the energy consumption of offloading computation are still critical issues to be solved.To address the above problems,this thesis studies the secure communication technology for UAV-assisted edge offloading computation,and achieves performance improvement in both security and energy consumption of the system by optimizing the UAV trajectory and formulating the associated offloading strategy while meeting the mission delay requirements.Based on this,the main work and contributions of this thesis are summarized as follows:A.A secure UAV offloading system based on the secrecy rate-energy consumption tradeoff is proposed for the average secrecy rate and user energy consumption tradeoff problem of the UAV-assisted MEC system.First,the multi-objective optimization problem of maximizing the secure secrecy rate and minimizing the user-side energy consumption is determined by analyzing the communication and computational offloading models of this offloading system.Subsequently,an alternating algorithm based on the block coordinate descent method is proposed to iteratively optimize the objective problem for parameters such as UAV trajectory,UAV jamming power,users’ offloading power,user-UAV association,and offloading strategy.Finally,the comparison simulation with the benchmark algorithm illustrates that the proposed optimization algorithm can significantly improve the system secrecy rate,effectively reduce the userside energy consumption and UAV flight energy consumption,and achieve an efficient and safe computational offloading service while safeguarding the task delay requirements.B.To overcome the problem that data transmission links become the bottleneck for the performance enhancement of secure offloading computational systems in complex scenarios,this thesis proposes an intelligent reflective surface-assisted UAV-MEC secure offloading system.First,by establishing communication,computation,cache,and energy consumption models,the minimized total system energy consumption objective function is proposed.Due to the non-convexity of this objective function,this thesis then designs a joint optimization algorithm based on convex approximation algorithm and block coordinate descent method to optimize the UAV trajectory,user association,caching and offloading strategies,and intelligent reflective surface coefficient matrix variables to achieve the objective of minimizing energy consumption under the condition of satisfying the mission processing time delay.Finally,the simulation results illustrate the efficiency of the proposed algorithm,and also show that the caching strategy and the emerging reflective surface technology play a positive role in improving both the computational and safety performance of the UAV-assisted MEC system.In summary,this thesis addresses the critical issues of secure communication systems for UAV-assisted edge offloading computation,proposes feasible solutions for optimizing system performance according to the challenges in current research,and verifies the effectiveness of the proposed solutions based on theoretical analysis and practical simulations,which provides some programmatic support for secure communication technologies for UAV-assisted edge offload computing.