  In this paper, a semantic-aware joint communication and computation resource
allocation framework is proposed for mobile edge computing (MEC) systems. In
the considered system, each terminal device (TD) has a computation task, which
needs to be executed by offloading to the MEC server. To further decrease the
transmission burden, each TD sends the small-size extracted semantic
information of tasks to the server instead of the large-size raw data. An
optimization problem of joint semantic-aware division factor, communication and
computation resource management is formulated. The problem aims to minimize the
maximum execution delay of all TDs while satisfying energy consumption
constraints. The original non-convex problem is transformed into a convex one
based on the geometric programming and the optimal solution is obtained by the
alternating optimization algorithm. Moreover, the closed-form optimal solution
of the semantic extraction factor is derived. Simulation results show that the
proposed algorithm yields up to 37.10% delay reduction compared with the
benchmark algorithm without semantic-aware allocation. Furthermore, small
semantic extraction factors are preferred in the case of large task sizes and
poor channel conditions.
