Related papers: Generative Channel Knowledge Base With Environment…
Integrated sensing and communication (ISAC) increasingly exposes a gap in today's channel modeling. Efficient statistical models focus on coarse communication-centric metrics, and therefore miss the weak but critical multipath signatures…
Semantic communication has gained significant attention from researchers as a promising technique to replace conventional communication in the next generation of communication systems, primarily due to its ability to reduce communication…
Deep Joint Source-Channel Coding (Deep-JSCC) has emerged as a promising semantic communication approach for wireless image transmission by jointly optimizing source and channel coding using deep learning techniques. However, traditional…
Joint source-channel coding (JSCC) offers a promising avenue for enhancing transmission efficiency by jointly incorporating source and channel statistics into the system design. A key advancement in this area is the deep joint source and…
A novel generative site-specific beamforming (GenSSBF) framework is proposed, which integrates a site-information-maximizing (SIM) codebook with a conditional flow matching (CFM)-based beam generator. By this framework, the site-specific…
Semantic communication is designed to tackle issues like bandwidth constraints and high latency in communication systems. However, in complex network topologies with multiple users, the enormous combinations of client data and channel state…
Channel knowledge map (CKM) is a promising technique that enables environment-aware wireless networks by utilizing location-specific channel prior information to improve communication and sensing performance. A fundamental problem for CKM…
Generative joint source-channel coding (GJSCC) has emerged as a new Deep JSCC paradigm for achieving high-fidelity and robust image transmission under extreme wireless channel conditions, such as ultra-low bandwidth and low signal-to-noise…
Channel knowledge map (CKM) is a promising technique to achieve environment-aware wireless communication and sensing. Constructing the complete CKM based on channel knowledge observations at sparse locations is a fundamental problem for…
Semantic communication (SemCom) has emerged as a transformative paradigm for future 6G networks, offering task-oriented and meaning-aware transmission that fundamentally redefines traditional bit-centric design. Recognized by leading…
The ability to construct channel knowledge map (CKM) with high precision is essential for environment awareness in 6G wireless systems. However, most existing CKM construction methods formulate the task as an image super-resolution or…
Most existing semantic communication systems employ analog modulation, which is incompatible with modern digital communication systems. Although several digital transmission approaches have been proposed to address this issue, an end-to-end…
Semantic communication (SemCom) is expected to be a core paradigm in future communication networks, yielding significant benefits in terms of spectrum resource saving and information interaction efficiency. However, the existing SemCom…
Joint source-channel coding (JSCC) is an effective approach for semantic communication. However, current JSCC methods are difficult to integrate with existing communication network architectures, where application and network providers are…
Despite significant advancements in traditional syntactic communications based on Shannon's theory, these methods struggle to meet the requirements of 6G immersive communications, especially under challenging transmission conditions. With…
Semantic communication (SemCom) aims to convey the intended meaning of messages rather than merely transmitting bits, thereby offering greater efficiency and robustness, particularly in resource-constrained or noisy environments. In this…
Channel knowledge map (CKM) inference across base stations (BSs) is the key to achieving efficient environmentaware communications. This paper proposes an environmentaware cross-BS CKM inference method called BS-1-to-N based on the…
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…
In recent years, the Transformer architecture has achieved outstanding performance across a wide range of tasks and modalities. Token is the unified input and output representation in Transformer-based models, which has become a fundamental…
As one of the potential key technologies of 6G, semantic communication is still in its infancy and there are many open problems, such as semantic entropy definition and semantic channel coding theory. To address these challenges, we…