Intelligent Reflecting Surface Assisted High-Mobile Edge Computing System: Joint Optimization of Computation and Communication

Mobile edge computing(MEC) can effectively cope with compute-intensive applications, but its full play is limited by the communication environment. Intelligent reflecting surface (IRS), as one of the key technologies of 6G, has the ability to improve the transmission environment and effectively improve the performance of the communication system. In this paper, the IRS-assisted MEC system with high-mobile users (H-MEC) is considered. Based on the system model, the minimizing total energy consumption is investigated. Partial offload mode is adopted to jointly optimize computation and communication for H-MEC system. The minimizing total energy consumption is a complex non-convex problem and the variables are coupled to each other, which is decomposed into five subproblems by the method of block coordinate descent (BCD) and the corresponding algorithms are proposed. Specifically, the quadratic transformation is used to deal with the fractional term, and the Lagrange dual transformation is used to deal with the logarithmic term. A low-complexity iterative algorithm is then used to alternately optimize the computation and communication settings. Finally, the effects of system parameters such as the number of users and antennas, the computing task size and the bandwidth of the system on the total energy consumption are investigated. The results show that the proposed algorithms for IRS assisted H-MEC system can effectively improve the system performance as to energy consumption.