Recent advances in artificial intelligence (AI), coupled with a surge in
training data, have led to the widespread use of AI for digital content
generation, with ChatGPT serving as a representative example. Despite the
increased efficiency and diversity, the inherent instability of AI models poses
a persistent challenge in guiding these models to produce the desired content
for users. In this paper, we introduce an integration of wireless perception
(WP) with AI-generated content (AIGC) and propose a unified WP-AIGC framework
to improve the quality of digital content production. The framework employs a
novel multi-scale perception technology to read user's posture, which is
difficult to describe accurately in words, and transmits it to the AIGC model
as skeleton images. Based on these images and user's service requirements, the
AIGC model generates corresponding digital content. Since the production
process imposes the user's posture as a constraint on the AIGC model, it makes
the generated content more aligned with the user's requirements. Additionally,
WP-AIGC can also accept user's feedback, allowing adjustment of computing
resources at edge server to improve service quality. Experiments results verify
the effectiveness of the WP-AIGC framework, highlighting its potential as a
novel approach for guiding AI models in the accurate generation of digital
content.

本文提出了一种新方法，将无线感知技术与人工智能生成的内容相结合，提出了一个统一的无线感知 - 人工智能生成内容框架，以改善数字内容生产的质量，在服务需求的基础上生成相应的数字内容。该框架能够根据用户的姿势作为约束生成内容，并能接受用户的反馈，从而调整边缘服务器上的计算资源以提高服务质量。实验结果验证了该框架的有效性，凸显了其在准确生成数字内容方面的潜力。