Abstract
Generative foundation models can revolutionize the design of semantic
communication (SemCom) systems allowing high fidelity exchange of semantic
information at ultra low rates. In this work, a generative SemCom framework
with pretrained foundation models is proposed, where both uncoded
forward-with-error and coded discard-with-error schemes are developed for the
semantic decoder. To characterize the impact of transmission reliability on the
perceptual quality of the regenerated signal, their mathematical relationship
is analyzed from a rate-distortion-perception perspective, which is proved to
be non-decreasing. The semantic values are defined to measure the semantic
information of multimodal semantic features accordingly. We also investigate
semantic-aware power allocation problems aiming at power consumption
minimization for ultra low rate and high fidelity SemComs. To solve these
problems, two semantic-aware power allocation methods are proposed by
leveraging the non-decreasing property of the perception-error relationship.
Numerically, perception-error functions and semantic values of semantic data
streams under both schemes for image tasks are obtained based on the Kodak
dataset. Simulation results show that our proposed semanticaware method
significantly outperforms conventional approaches, particularly in the
channel-coded case (up to 90% power saving).