Satellite-Terrestrial Integrated Networks-Assisted Vehicular Task Offloading with THz-RF Transmission

In this paper, we propose a Satellite-Terrestrial Integrated Network (STIN) assisted vehicular task offloading leveraging hybrid terahertz (THz) and radio frequency (RF) communication technologies. Task offloading for satellite edge computing is enabled by THz communication using the orthogonal frequency division multiple access (OFDMA) technique. For terrestrial edge computing, we employ non-orthogonal multiple access (NOMA) and vehicle clustering to realize task offloading. We formulate a non-convex optimization problem aimed at maximizing computation efficiency by jointly optimizing bandwidth allocation, task allocation and power allocation. To address this non-convex optimization problem, we decompose the original problem into three sub-problems and solve them using an alternating iterative optimization approach. For the subproblem of task allocation, we solve it by linear programming. The subproblem of bandwidth allocation of OFDMA and the sub-problem of power allocation of NOMA are solved by quadratic transformation method. Finally, the simulation results show that our proposed scheme significantly enhances the computation efficiency of the STIN-based vehicular task offloading compared with the benchmark schemes.