Related papers: Modeling and Performance Analysis for Semantic Com…
Semantic communication (SemCom) aims to enhance the resource efficiency of next-generation networks by transmitting the underlying meaning of messages, focusing on information relevant to the end user. Existing literature on SemCom…
An end-to-end communications system based on Orthogonal Frequency Division Multiplexing (OFDM) is modeled as an autoencoder (AE) for which the transmitter (coding and modulation) and receiver (demodulation and decoding) are represented as…
Improving the efficiency of state-of-the-art methods in semantic segmentation requires overcoming the increasing computational cost as well as issues such as fusing semantic information from global and local contexts. Based on the recent…
Goal-oriented semantic communication (SC) aims to revolutionize communication systems by transmitting only task-essential information. However, current approaches face challenges such as joint training at transceivers, leading to redundant…
Semantic communication (SemCom) is emerging as a key technology for future sixth-generation (6G) systems. Unlike traditional bit-level communication (BitCom), SemCom directly optimizes performance at the semantic level, leading to superior…
In the era of 6G, with compelling visions of intelligent transportation systems and digital twins, remote surveillance is poised to become a ubiquitous practice. Substantial data volume and frequent updates present challenges in wireless…
This paper explores the performance of reconfigurable intelligent surface (RIS) assisted spatial modulation (SM) downlink communication systems, focusing on the average bit error probability (ABEP). Notably, in scenarios with a large number…
Wireless communication has achieved great success in the past several decades. The challenge is of improving bandwidth with limited spectrum and power consumption, which however has gradually become a bottleneck with evolution going on. The…
Standard language models employ unique, monolithic embeddings for each token, potentially limiting their ability to capture the multifaceted nature of word meanings. We investigate whether tokens can be more effectively represented through…
Semantic communications are expected to enable the more effective delivery of meaning rather than a precise transfer of symbols. In this paper, we propose an end-to-end deep neural network-based architecture for image transmission and…
Focusing on the downlink, we consider a base station (BS) and the cell it covers. The Superposition Coding (SC), also referred to as Non Orthogonal Multiple Access (NOMA), is implemented. We propose an analytical model of the wireless cell…
Deep learning (DL) based semantic communication methods have been explored for the efficient transmission of images, text, and speech in recent years. In contrast to traditional wireless communication methods that focus on the transmission…
Advancements in 6G wireless technology have elevated the importance of beamforming, especially for attaining ultra-high data rates via millimeter-wave (mmWave) frequency deployment. Although promising, mmWave bands require substantial beam…
With the rapid development of Artificial Intelligent Internet of Things (AIoT), the image data from AIoT devices has been witnessing the explosive increasing. In this paper, a novel deep image semantic communication model is proposed for…
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…
Semantic communication is emerging as a key paradigm for 6G networks, where the goal is not to perfectly reconstruct bits but to preserve the meaning that matters for a given task. This shift can improve bandwidth efficiency, robustness,…
Semantic communications (SemComs) have emerged as a promising paradigm for joint data and task-oriented transmissions, combining the demands for both the bit-accurate delivery and end-to-end (E2E) distortion minimization. However, current…
Recently, learning-based semantic communication (SemCom) has emerged as a promising approach in the upcoming 6G network and researchers have made remarkable efforts in this field. However, existing works have yet to fully explore the…
This paper presents a Semantic Feature Multiple Access (SFMA) framework for multi-user semantic communication in downlink wireless systems. By extending SwinJSCC to a two-user superimposition paradigm, SFMA enables simultaneous semantic…
A radical paradigm shift of wireless networks from ``connected things'' to ``connected intelligence'' undergoes, which coincides with the Shanno and Weaver's envisions: Communications will transform from the technical level to the semantic…