Mechanism Design for Semantic Communication in UAV-Assisted Metaverse: A Combinatorial Auction Approach.

Metaverse enables users to experience a virtual space that resembles the real world. In the Metaverse, virtual service providers (VSPs) maintain digital twins (DTs) of real-world entities to offer innovative services such as virtual conferences and tourism. However, to provide a realistic experience, VSPs need to collect up-to-date and relevant data, which is latency-sensitive and resource-intensive, from edge devices such as unmanned aerial vehicles (UAVs). To address this challenge, we propose a semantic communication framework that leverages extraction and trading of scene graphs to reduce communication costs and motivate data transfer for Metaverse services. In the framework, we propose a semantic communication system where data for building DTs is encoded as semantic information, such as scene graphs. VSPs can use these graphs to build or update their DTs. To facilitate data trading between VSPs and edge nodes, we introduce a combinatorial auction-based incentive mechanism where we model the valuation of semantic data based on relatedness, freshness, and semantic values. We measure the relatedness based on the similarity between targeted objects of VSPs and the objects present in the real-world data. We use the age of information (AoI) to quantify data freshness and evaluate the semantic value using the information richness of the scene graphs. Simulation results show that our system can maintain the model's mean recall performance using only 12.5% of features during transmission. Our mechanism increases the average update frequency effectively. The theoretical analysis proves that the proposed mechanism guarantees the desired properties of individual rationality and incentive compatibility.