Recently, deep learning (DL) based semantic communication systems have shown great
potential to improve transmission efficiency in various tasks. However, the coexisting …

In this paper, we propose an adaptive semantic resource allocation paradigm with semantic-
bit quantization (SBQ) compatible with existing wireless communications, where the …

With the aim of accomplishing intelligence tasks, semantic communications transmit task-
related information only, yielding significant performance gains over conventional …

Semantic communication has been regarded as a promising technology to serve upcoming
intelligent applications. However, few studies have addressed the problem of resource …

For cyber-physical systems in the 6G era, semantic communications connecting distributed
devices for dynamic control and remote state estimation are required to guarantee …

As a new communication paradigm, neural network-driven semantic communication
(SemCom) has demonstrated considerable promise in enhancing resource efficiency by …

In this work, we investigate the challenging problem of on-demand semantic communication
over heterogeneous wireless networks. We propose a fidelity-adjustable semantic …

Although existing semantic communication systems have achieved great success, they have
not considered that the channel is time-varying wherein deep fading occurs occasionally …

In this paper, a semantic communication framework is proposed for wireless networks. In the
proposed framework, a base station (BS) extracts the semantic information from textual data …

Semantic communication (SemCom) has recently been considered a promising solution to
guarantee high resource utilization and transmission reliability for future wireless networks …