Training-Free Multi-User Generative Semantic Communications via Null-Space Diffusion Sampling

TL;DR

This paper introduces a training-free, multi-user semantic communication framework using null-space diffusion sampling, enabling content regeneration at receivers with minimal transmitted information.

Contribution

It proposes a novel multi-user generative semantic communication system leveraging diffusion models, moving beyond single-user approaches and traditional transmission strategies.

Findings

Diffusion models effectively regenerate missing content at receivers.

The framework reduces the amount of transmitted data needed for content reconstruction.

Experimental results demonstrate the system's potential for next-generation GenAI communications.

Abstract

In recent years, novel communication strategies have emerged to face the challenges that the increased number of connected devices and the higher quality of transmitted information are posing. Among them, semantic communication obtained promising results especially when combined with state-of-the-art deep generative models, such as large language or diffusion models, able to regenerate content from extremely compressed semantic information. However, most of these approaches focus on single-user scenarios processing the received content at the receiver on top of conventional communication systems. In this paper, we propose to go beyond these methods by developing a novel generative semantic communication framework tailored for multi-user scenarios. This system assigns the channel to users knowing that the lost information can be filled in with a diffusion model at the receivers. Under this innovative perspective, OFDMA systems should not aim to transmit the largest part of information, but solely the bits necessary to the generative model to semantically regenerate the missing ones. The thorough experimental evaluation shows the capabilities of the novel diffusion model and the effectiveness of the proposed framework, leading towards a GenAI-based next generation of communications.