TY - JOUR
T1 - Joint MEC and ISAC Design in HetNets with SIM-Aided Wireless Backhaul
AU - Chen, Jinsong
AU - Niu, Jinping
AU - Lyu, Maiqian
AU - Gu, Tao
AU - Fan, Jiancun
AU - Li, Yanyan
N1 - Publisher Copyright:
© 2001-2012 IEEE.
PY - 2026
Y1 - 2026
N2 - This work focuses on the integrated sensing, communication, and computation (SCC) for Internet of Vehicles (IoV) in wireless-backhaul heterogeneous networks (HetNets). The wireless backhaul performance of HetNets is typically limited by constrained capacity and severe interference. To address these challenges, stacked intelligent metasurfaces (SIM) is introduced into the wireless-backhaul HetNets. In the SIM-assisted IoV HetNet SCC system, a multi-objective optimization problem is formulated with the objectives of minimizing computation offloading energy consumption and maximizing the sensing beampattern gain of vehicular terminals (VTs). An alternating optimization framework is proposed to jointly optimize VTs computation offloading, SIM passive beamforming, sensing and communication precoding, and mobile edge computing (MEC) resource allocation. Simulation results demonstrate that the proposed scheme effectively balances energy efficiency and sensing performance, achieving significant improvements in both overall energy efficiency and sensing capability compared with conventional approaches.
AB - This work focuses on the integrated sensing, communication, and computation (SCC) for Internet of Vehicles (IoV) in wireless-backhaul heterogeneous networks (HetNets). The wireless backhaul performance of HetNets is typically limited by constrained capacity and severe interference. To address these challenges, stacked intelligent metasurfaces (SIM) is introduced into the wireless-backhaul HetNets. In the SIM-assisted IoV HetNet SCC system, a multi-objective optimization problem is formulated with the objectives of minimizing computation offloading energy consumption and maximizing the sensing beampattern gain of vehicular terminals (VTs). An alternating optimization framework is proposed to jointly optimize VTs computation offloading, SIM passive beamforming, sensing and communication precoding, and mobile edge computing (MEC) resource allocation. Simulation results demonstrate that the proposed scheme effectively balances energy efficiency and sensing performance, achieving significant improvements in both overall energy efficiency and sensing capability compared with conventional approaches.
KW - communication
KW - computation
KW - heterogeneous networks (HetNets)
KW - integrated sensing
KW - internet of vehicles (IoV)
KW - Mobile edge computing (MEC)
KW - stacked intelligent metasurface (SIM)
UR - https://www.scopus.com/pages/publications/105043066884
U2 - 10.1109/JSEN.2026.3702953
DO - 10.1109/JSEN.2026.3702953
M3 - 文章
AN - SCOPUS:105043066884
SN - 1530-437X
JO - IEEE Sensors Journal
JF - IEEE Sensors Journal
ER -