Semantic communication (SemCom) and edge computing are two disruptive
solutions to address emerging requirements of huge data communication,
bandwidth efficiency and low latency data processing in Metaverse. However,
edge computing resources are often provided by computing service providers and
thus it is essential to design appealingly incentive mechanisms for the
provision of limited resources. Deep learning (DL)- based auction has recently
proposed as an incentive mechanism that maximizes the revenue while holding
important economic properties, i.e., individual rationality and incentive
compatibility. Therefore, in this work, we introduce the design of the DLbased
auction for the computing resource allocation in SemComenabled Metaverse.
First, we briefly introduce the fundamentals and challenges of Metaverse.
Second, we present the preliminaries of SemCom and edge computing. Third, we
review various incentive mechanisms for edge computing resource trading.
Fourth, we present the design of the DL-based auction for edge resource
allocation in SemCom-enabled Metaverse. Simulation results demonstrate that the
DL-based auction improves the revenue while nearly satisfying the individual
rationality and incentive compatibility constraints.Comment: 7 pages, 5 figure