Related papers: Digital Semantic Communications: An Alternating Mu…

In this work, a self-attention based conditional generative adversarial network (SA-cGAN) framework for the sixth generation (6G) semantic communication system is proposed, explicitly designed to balance the trade-off between distortion…

Multi-agent systems (MAS) are a promising solution for autonomous exploration tasks in hazardous or remote environments, such as planetary surveys. In such settings, communication among agents is essential to ensure collaborative task…

In next-generation wireless networks, supporting real-time applications such as augmented reality, autonomous driving, and immersive Metaverse services demands stringent constraints on bandwidth, latency, and reliability. Existing semantic…

This work designs a novel semantic communication (SemCom) framework for the next-generation wireless network to tackle the challenges of unnecessary transmission of vast amounts that cause high bandwidth consumption, more latency, and…

Rapid LLM advancements heighten fake news risks by enabling the automatic generation of increasingly sophisticated misinformation. Previous detection methods, including fine-tuned small models or LLM-based detectors, often struggle with its…

The rapid advancement of generative artificial intelligence has spurred innovative approaches to semantic communication, giving rise to a new paradigm known as generative semantic communication (GSC). The integration of flexible cross-modal…

This article investigates the exploitation of semantic communications in multi-user networks. We propose a novel heterogeneous semantic and bit multi-user framework for providing flawless, customized, and intelligent information…

As satellite communications play an increasingly important role in future wireless networks, the issue of limited link budget in satellite systems has attracted significant attention in current research. Although semantic communications…

Semantic communications (SemComs) have been considered as a promising solution to reduce the amount of transmitted information, thus paving the way for more energy-and spectrum-efficient wireless networks. Nevertheless, SemComs rely heavily…

Semantic communication has emerged as a pillar for the next generation of communication systems due to its capabilities in alleviating data redundancy. Most semantic communication systems are built upon advanced deep learning models whose…

To address the challenges of robust data transmission over complex time-varying channels, this paper introduces channel learning and enhanced adaptive reconstruction (CLEAR) strategy for semantic communications. CLEAR integrates deep joint…

Employing massive Mobile AI-Generated Content (AIGC) Service Providers (MASPs) with powerful models, high-quality AIGC services can become accessible for resource-constrained end users. However, this advancement, referred to as mobile AIGC,…

Open-vocabulary semantic segmentation aims to assign pixel-level labels to images across an unlimited range of classes. Traditional methods address this by sequentially connecting a powerful mask proposal generator, such as the Segment…

We investigate distributed multiple-input multiple-output (D-MIMO) integrated sensing and communication (ISAC) systems, in which multiple phase-synchronized access points (APs) jointly serve user equipments (UEs) while cooperatively…

The recent emergence of 6G raises the challenge of increasing the transmission data rate even further in order to overcome the Shannon limit. Traditional communication methods fall short of the 6G goals, paving the way for Semantic…

Semantic Communication (SC) is an emerging technology aiming to surpass the Shannon limit. Traditional SC strategies often minimize signal distortion between the original and reconstructed data, neglecting perceptual quality, especially in…

Task-Oriented Semantic Communication (TOSC) has been considered as a new communication paradigm to serve various samrt devices that depend on Artificial Intelligence (AI) tasks in future wireless networks. The existing TOSC frameworks rely…

This paper addresses the challenge of achieving security in semantic communication (SemCom) over a wiretap channel, where a legitimate receiver coexists with an eavesdropper experiencing a poorer channel condition. Despite previous efforts…

Semantic communication aims to convey meaning rather than bit-perfect reproduction, representing a paradigm shift from traditional communication. This paper investigates distribution learning in semantic communication where receivers must…

Semantic communication technology emerges as a pivotal bridge connecting AI with classical communication. The current semantic communication systems are generally modeled as an Auto-Encoder (AE). AE lacks a deep integration of AI principles…