TY - JOUR
T1 - Vehicular Multi-Tier Distributed Computing With Hybrid THz-RF Transmission in Satellite–Terrestrial Integrated Networks
AU - Zhang, Ni
AU - Wang, Kunlun
AU - Chen, Wen
AU - Xu, Jing
AU - Nallanathan, Arumugam
N1 - Publisher Copyright:
© 2002-2012 IEEE.
PY - 2026
Y1 - 2026
N2 - In this paper, we propose a Satellite-Terrestrial Integrated Network (STIN) assisted vehicular multi-tier distributed computing (VMDC) system 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, subchannel-vehicle matching and power allocation. To address this non-convex optimization problem, we decompose the original problem into four sub-problems and solve them using an alternating iterative optimization approach. For the subproblem of task allocation, we solve it by linear programming. To solve the subproblem of sub-channel allocation, we exploit many-to-one matching theory to obtain the result. The subproblem of bandwidth allocation of OFDMA and the subproblem 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 VMDC system compared with the benchmark schemes.
AB - In this paper, we propose a Satellite-Terrestrial Integrated Network (STIN) assisted vehicular multi-tier distributed computing (VMDC) system 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, subchannel-vehicle matching and power allocation. To address this non-convex optimization problem, we decompose the original problem into four sub-problems and solve them using an alternating iterative optimization approach. For the subproblem of task allocation, we solve it by linear programming. To solve the subproblem of sub-channel allocation, we exploit many-to-one matching theory to obtain the result. The subproblem of bandwidth allocation of OFDMA and the subproblem 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 VMDC system compared with the benchmark schemes.
KW - Satellite-terrestrial integrated networks (STIN)
KW - alternating optimization algorithm (AO)
KW - many-to-one matching
KW - non-orthogonal multiple access (NOMA)
KW - orthogonal frequency division multiple access (OFDMA)
KW - task offloading
UR - https://www.scopus.com/pages/publications/105024602999
U2 - 10.1109/TWC.2025.3638160
DO - 10.1109/TWC.2025.3638160
M3 - 文章
AN - SCOPUS:105024602999
SN - 1536-1276
VL - 25
SP - 9891
EP - 9905
JO - IEEE Transactions on Wireless Communications
JF - IEEE Transactions on Wireless Communications
ER -