TY  - EJOU
AU  - Zhang, Ying 
AU  - Niu, Weiming 
AU  - Xiu, Supu 
AU  - Mu, Guangchen 

TI  - Energy Efficiency Maximization in Mobile Edge Computing Networks via IRS assisted UAV Communications
T2  - Computer Modeling in Engineering \& Sciences

PY  - 2024
VL  - 138
IS  - 2
SN  - 1526-1506

AB  - In this paper, we investigate the energy efficiency maximization for mobile edge computing (MEC) in intelligent reflecting surface (IRS) assisted unmanned aerial vehicle (UAV) communications. In particular, UAV can collect the computing tasks of the terrestrial users and transmit the results back to them after computing. We jointly optimize the users’ transmitted beamforming and uploading ratios, the phase shift matrix of IRS, and the UAV trajectory to improve the energy efficiency. The formulated optimization problem is highly non-convex and difficult to be solved directly. Therefore, we decompose the original problem into three sub-problems. We first propose the successive convex approximation (SCA) based method to design the beamforming of the users and the phase shift matrix of IRS, and apply the Lagrange dual method to obtain a closed-form expression of the uploading ratios. For the trajectory optimization, we propose a block coordinate descent (BCD) based method to obtain a local optimal solution. Finally, we propose the alternating optimization (AO) based overall algorithm and analyzed its complexity to be equivalent or lower than existing algorithms. Simulation results show the superiority of the proposed method compared with existing schemes in energy efficiency.
KW  - Mobile edge computing (MEC); unmanned aerial vehicle (UAV); intelligent reflecting surface (IRS); energy efficiency

DO  - 10.32604/cmes.2023.030114