Human-in-the-Loop Virtual Reality Offloading Scheme in Wireless 6G Terahertz Networks

Upcoming sixth-generation networks have to be carefully designed to offer support to a wide range of human- centric applications, typically computationally intensive and heavily dependent on human perception. This paper proposes a human-in-the-loop-based resource allocation approach found on the joint use of matching theory and stochastic network calculus principles to efficiently address tasks offloading issues within a sixth-generation network environment. The considered matching game approach is characterized by externalities, whose stability is properly discussed here. In particular, by focusing on virtual reality services, the paper aims at maximizing the average service reliability in terms of ability in guaranteeing a proper quality of experience target, i.e., keeping the end-to-end delay below a suitable threshold, by the proper exploitation of the human cognitive limitations. Finally, the effectiveness of the proposed human-in-the-loop-based resource allocation approach is verified by proving comparisons with simulation results and conventional brain-agnostic strategies.