  In the era of 6G, featuring compelling visions of digital twins and
metaverses, Extended Reality (XR) has emerged as a vital conduit connecting the
digital and physical realms, garnering widespread interest. Ensuring a fully
immersive wireless XR experience stands as a paramount technical necessity,
demanding the liberation of XR from the confines of wired connections. In this
paper, we first introduce the technologies applied in the wireless XR domain,
delve into their benefits and limitations, and highlight the ongoing
challenges. We then propose a novel deployment framework for a broad XR
pipeline, termed "GeSa-XRF", inspired by the core philosophy of Semantic
Communication (SemCom) which shifts the concern from "how" to transmit to
"what" to transmit. Particularly, the framework comprises three stages: data
collection, data analysis, and data delivery. In each stage, we integrate
semantic awareness to achieve streamlined transmission and employ Generative
Artificial Intelligence (GAI) to achieve collaborative refinements. For the
data collection of multi-modal data with differentiated data volumes and
heterogeneous latency requirements, we propose a novel SemCom paradigm based on
multi-modal fusion and separation and a GAI-based robust superposition scheme.
To perform a comprehensive data analysis, we employ multi-task learning to
perform the prediction of field of view and personalized attention and discuss
the possible preprocessing approaches assisted by GAI. Lastly, for the data
delivery stage, we present a semantic-aware multicast-based delivery strategy
aimed at reducing pixel level redundant transmissions and introduce the GAI
collaborative refinement approach. The performance gain of the proposed
GeSa-XRF is preliminarily demonstrated through a case study.
