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相关论文: Transmission of Spatio-Temporal Correlated Sources…

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In this paper, communication of a Multivariate Gaussian over a Gaussian Multiple Access Channel is studied. Distributed zero-delay joint source-channel coding (JSCC) solutions to the problem are given. Both nonlinear and linear approaches…

A joint source-channel coding (JSCC) scheme based on hybrid digital/analog coding is proposed for the transmission of correlated sources over discrete-memoryless two-way channels (DM-TWCs). The scheme utilizes the correlation between the…

信息论 · 计算机科学 2020-08-13 Jian-Jia Weng , Fady Alajaji , Tamás Linder

In this paper, delay-free, low complexity, joint source-channel coding (JSCC) for transmission of two correlated Gaussian memoryless sources over a Gaussian Multiple Access Channel (GMAC) is considered. The main contributions of the paper…

In this paper we address the problem of transmission of correlated sources over a fast fading multiple access channel (MAC) with partial channel state information available at both the encoders and the decoder. We provide sufficient…

信息论 · 计算机科学 2009-08-11 R Rajesh , Vinod Sharma

This paper investigates distributed source-channel coding for correlated image semantic transmission over wireless channels. In this setup, correlated images at different transmitters are separately encoded and transmitted through dedicated…

信息论 · 计算机科学 2025-06-10 Yufei Bo , Meixia Tao , Kai Niu

This paper investigates distributed joint source-channel coding (JSCC) for correlated image semantic transmission over wireless channels. In this setup, correlated images at different transmitters are separately encoded and transmitted…

信息论 · 计算机科学 2025-03-28 Yufei Bo , Meixia Tao

We consider the transmission of spatially correlated analog information in a wireless sensor network (WSN) through fading single-input and multiple-output (SIMO) multiple access channels (MACs) with low-latency requirements. A lattice-based…

信息论 · 计算机科学 2024-01-31 Pedro Suárez-Casal , Óscar Fresnedo , Darian Pérez-Adán , Luis Castedo

We present a deep learning based joint source channel coding (JSCC) scheme for wireless image transmission over multipath fading channels with non-linear signal clipping. The proposed encoder and decoder use convolutional neural networks…

信号处理 · 电气工程与系统科学 2021-05-25 Mingyu Yang , Chenghong Bian , Hun-Seok Kim

We propose an adaptive lossy joint source-channel coding (JSCC) scheme for sending correlated sources over two-terminal discrete-memoryless two-way channels (DM-TWCs). The main idea is to couple the independent operations of the terminals…

信息论 · 计算机科学 2020-06-29 Jian-Jia Weng , Fady Alajaji , Tamás Linder

An adaptive joint source-channel coding (JSCC) scheme is presented for transmitting correlated sources over discrete-memoryless two-way channels subject to distortion constraints. The proposed JSCC scheme makes use of the previously…

信息论 · 计算机科学 2020-08-13 Jian-Jia Weng , Fady Alajaji , Tamás Linder

We study the problem of deep joint source-channel coding (D-JSCC) for correlated image sources, where each source is transmitted through a noisy independent channel to the common receiver. In particular, we consider a pair of images…

信息论 · 计算机科学 2022-01-26 Sixian Wang , Ke Yang , Jincheng Dai , Kai Niu

This work is concerned with robust distributed multi-view image transmission over a severe fading channel with imperfect channel state information (CSI), wherein the sources are slightly correlated. Since the signals are further distorted…

信号处理 · 电气工程与系统科学 2026-04-15 Biao Dong , Bin Cao , Guan Gui , Qinyu Zhang

We consider the problem of transmission of several distributed sources over a multiple access channel (MAC) with side information at the sources and the decoder. Source-channel separation does not hold for this channel. Sufficient…

信息论 · 计算机科学 2008-03-11 R. Rajesh , Vinod Sharma

A general lossless joint source-channel coding (JSCC) scheme based on linear codes and random interleavers for multiple-access channels (MACs) is presented and then analyzed in this paper. By the information-spectrum approach and the…

信息论 · 计算机科学 2009-03-31 Shengtian Yang , Yan Chen , Peiliang Qiu

To address the challenges of wireless video transmission over multipath fading channels, we propose a robust deep joint source-channel coding (DeepJSCC) framework by effectively exploiting temporal redundancy and incorporating robust…

图像与视频处理 · 电气工程与系统科学 2026-01-21 Bohuai Xiao , Jian Zou , Fanyang Meng , Wei Liu , Yongsheng Liang

We investigate joint source channel coding (JSCC) for wireless image transmission over multipath fading channels. Inspired by recent works on deep learning based JSCC and model-based learning methods, we combine an autoencoder with…

信号处理 · 电气工程与系统科学 2021-09-14 Mingyu Yang , Chenghong Bian , Hun-Seok Kim

Recent works have shown that modern machine learning techniques can provide an alternative approach to the long-standing joint source-channel coding (JSCC) problem. Very promising initial results, superior to popular digital schemes that…

图像与视频处理 · 电气工程与系统科学 2022-06-17 Tze-Yang Tung , David Burth Kurka , Mikolaj Jankowski , Deniz Gunduz

As one novel approach to realize end-to-end wireless image semantic transmission, deep learning-based joint source-channel coding (deep JSCC) method is emerging in both deep learning and communication communities. However, current deep JSCC…

计算机视觉与模式识别 · 计算机科学 2022-05-27 Jun Wang , Sixian Wang , Jincheng Dai , Zhongwei Si , Dekun Zhou , Kai Niu

We present a decode-and-forward transmission scheme based on spatially-coupled low-density parity-check (SC-LDPC) codes for a network consisting of two (possibly correlated) sources, one relay, and one destination. The links between the…

信息论 · 计算机科学 2014-02-17 Stefan Schwandter , Alexandre Graell i Amat , Gerald Matz

Semantic- and task-oriented communication has emerged as a promising approach to reducing the latency and bandwidth requirements of next-generation mobile networks by transmitting only the most relevant information needed to complete a…

信息论 · 计算机科学 2024-09-27 Deniz Gündüz , Michèle A. Wigger , Tze-Yang Tung , Ping Zhang , Yong Xiao
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