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In this paper, we introduce a deep multiple description coding (MDC) framework optimized by minimizing multiple description (MD) compressive loss. First, MD multi-scale-dilated encoder network generates multiple description tensors, which…

Computer Vision and Pattern Recognition · Computer Science 2020-01-14 Lijun Zhao , Huihui Bai , Anhong Wang , Yao Zhao

We consider transmitting a source across a pair of independent, non-ergodic channels with random states (e.g., slow fading channels) so as to minimize the average distortion. The general problem is unsolved. Hence, we focus on comparing two…

Information Theory · Computer Science 2009-09-29 J. Nicholas Laneman , Emin Martinian , Gregory W. Wornell , John G. Apostolopoulos

Some state-of-art multimedia source encoders produce embedded source bit streams that upon the reliable reception of only a fraction of the total bit stream, the decoder is able reconstruct the source up to a basic quality. Reliable…

Multimedia · Computer Science 2014-03-04 Suayb S. Arslan

This paper extends the well-known source coding problem of multiple descriptions, in its general and basic setting, to analog source-channel coding scenarios. Encoding-decoding functions that optimally map between the (possibly continuous…

Information Theory · Computer Science 2015-10-05 Mustafa Said Mehmetoglu , Emrah Akyol , Kenneth Rose

We consider the detection of correlated information sources in the ubiquitous Code-Division Multiple-Access (CDMA) scheme. We propose a message-passing based scheme for detecting correlated sources directly, with no need for source coding.…

Information Theory · Computer Science 2010-03-24 Hadar Efraim , Nadav Yacov , Ori Shental , Ido Kanter

We propose a novel joint decoding technique for distributed source-channel (DSC) coded systems for transmission of correlated binary Markov sources over additive white Gaussian noise (AWGN) channels. In the proposed scheme, relatively…

Information Theory · Computer Science 2013-08-02 Reza Asvadi , Tad Matsumoto , Markku Juntti

We present a joint source-channel multiple description (JSC-MD) framework for resource-constrained network communications (e.g., sensor networks), in which one or many deprived encoders communicate a Markov source against bit errors and…

Information Theory · Computer Science 2007-08-28 Xiaolin Wu , Xiaohan Wang , Zhe Wang

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…

Information Theory · Computer Science 2025-06-10 Yufei Bo , Meixia Tao , Kai Niu

In this paper, we consider a distributed reception scenario where a transmitter broadcasts a signal to multiple geographically separated receive nodes over fading channels, and each node forwards a few bits representing a processed version…

Information Theory · Computer Science 2015-06-19 Junil Choi , David J. Love , Patrick Bidigare

Data center networks (DCNs) require a low-cost, low-power optical transceiver to handle increased traffic from generative artificial intelligence, video streaming services, and more. Improving the required signal-to-noise ratio (RSNR) by…

Signal Processing · Electrical Eng. & Systems 2025-09-09 Takeshi Kakizaki , Masanori Nakamura , Fukutaro Hamaoka , Shuto Yamamoto , Etsushi Yamazaki

Diffusion models (DM) can gradually learn to remove noise, which have been widely used in artificial intelligence generated content (AIGC) in recent years. The property of DM for eliminating noise leads us to wonder whether DM can be…

Information Theory · Computer Science 2023-09-19 Tong Wu , Zhiyong Chen , Dazhi He , Liang Qian , Yin Xu , Meixia Tao , Wenjun Zhang

In this paper we propose a new framework for distributed source coding of structured sources, such as sparse signals. Our framework capitalizes on recent advances in the theory of linear inverse problems and signal representations using…

Information Theory · Computer Science 2020-12-02 Maxim Goukhshtein , Petros T. Boufounos , Toshiaki Koike-Akino , Stark C. Draper

In this paper, we design and analyze distributed vector quantization (VQ) for compressed measurements of correlated sparse sources over noisy channels. Inspired by the framework of compressed sensing (CS) for acquiring compressed…

Information Theory · Computer Science 2015-07-28 Amirpasha Shirazinia , Saikat Chatterjee , Mikael Skoglund

This paper investigates a unification of distributed source coding, multiple description coding, and source coding with side information at decoders. The equivalence between the multiple-decoder extension of distributed source coding with…

Information Theory · Computer Science 2024-10-28 Jun Muramatsu

Low-density parity-check (LDPC) codes with the parity-based approach for distributed joint source channel coding (DJSCC) with decoder side information is described in this paper. The parity-based approach is theoretical limit achievable.…

Information Theory · Computer Science 2014-04-10 Feng Cen

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…

Signal Processing · Electrical Eng. & Systems 2021-09-14 Mingyu Yang , Chenghong Bian , Hun-Seok Kim

We address the connection between the multiple-description (MD) problem and Delta-Sigma quantization. The inherent redundancy due to oversampling in Delta-Sigma quantization, and the simple linear-additive noise model resulting from…

Information Theory · Computer Science 2009-07-15 Jan Ostergaard , Ram Zamir

In this paper, we propose a fast decoder algorithm for uniquely decodable (errorless) code sets for overloaded synchronous optical code-division multiple-access (O-CDMA) systems. The proposed decoder is designed in a such a way that the…

Information Theory · Computer Science 2019-02-27 Michel Kulhandjian , Hovannes Kulhandjian , Claude D'Amours , Halim Yanikomeroglu , Gurgen Khachatrian

We consider the source-channel separation architecture for lossy source coding in communication networks. It is shown that the separation approach is optimal in two general scenarios, and is approximately optimal in a third scenario. The…

Information Theory · Computer Science 2013-12-04 Chao Tian , Jun Chen , Suhas Diggavi , Shlomo Shamai

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…

Information Theory · Computer Science 2022-01-26 Sixian Wang , Ke Yang , Jincheng Dai , Kai Niu
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