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We study the problem of secure joint source-channel coding for multimodal semantic sources transmitted over noisy wiretap channels. The source model consists of $m$ modalities (e.g., image, audio, and sensor data), all represented as random…

Information Theory · Computer Science 2026-05-26 Denis Kozlov , Mahtab Mirmohseni , Rahim Tafazolli

In this paper we study the nonasymptotic bounds of a special Joint Source-Channel Coding system with hierarchical source, where an observable source and an unobservable indirect source are required to be reconstructed. Namely, we focus on…

Information Theory · Computer Science 2026-03-17 Shuo Shao , Chao Qi , Jincheng Dai

We consider a point-to-point communication system, where in addition to the encoder and the decoder, there is a helper that observes non-causally the realization of the noise vector and provides a (lossy) rate-$R_{\mbox{\tiny h}}$…

Information Theory · Computer Science 2020-11-23 Neri Merhav

In this paper, we propose using a generic protograph to design joint source-channel codes (JSCCs). We present a generalized algorithm, called protograph extrinsic information transfer for JSCC algorithm (PEXIT-JSCC algorithm), for analyzing…

Information Theory · Computer Science 2022-10-19 Jia Zhan , Francis C. M. Lau

In this paper, we propose a high-efficiency deep joint source-channel coding (JSCC) method for video transmission based on conditional coding with asymmetric context. The conditional coding-based neural video compression requires to predict…

Image and Video Processing · Electrical Eng. & Systems 2026-01-13 Xuechen Chen , Junting Li , Chuang Chen , Hairong Lin , Yishen Li

We consider transmission of discrete memoryless sources (DMSes) across discrete memoryless channels (DMCs) using variable-length lossy source-channel codes with feedback. The reliability function (optimum error exponent) is shown to be…

Information Theory · Computer Science 2019-04-09 Lan V. Truong , Vincent Y. F. Tan

Semantic communications are expected to accomplish various semantic tasks with relatively less spectrum resource by exploiting the semantic feature of source data. To simultaneously serve both the data transmission and semantic tasks, joint…

Information Theory · Computer Science 2023-08-15 Jianhao Huang , Dongxu Li , Chuan Huang , Xiaoqi Qin , Wei Zhang

Deep joint source-channel coding (DeepJSCC) has emerged as a powerful paradigm for end-to-end semantic communications, jointly learning to compress and protect task-relevant features over noisy channels. However, existing DeepJSCC schemes…

A scenario involving a source, a channel, and a destination, where the destination is interested in {\em both} reliably reconstructing the message transmitted by the source and estimating with a fidelity criterion the state of the channel,…

Information Theory · Computer Science 2011-08-30 Wenyi Zhang , Satish Vedantam , Urbashi Mitra

Along with the proliferating research interest in Semantic Communication (SemCom), Joint Source Channel Coding (JSCC) has dominated the attention due to the widely assumed existence in efficiently delivering information semantics.…

Information Theory · Computer Science 2025-05-27 Tianqi Ren , Rongpeng Li , Ming-min Zhao , Xianfu Chen , Guangyi Liu , Yang Yang , Zhifeng Zhao , Honggang Zhang

This paper considers guessing-based decoders with abandonment for discrete memoryless channels in which all codewords have the same composition. This class of decoders rank-orders all input sequences in the codebook's composition class from…

Information Theory · Computer Science 2025-08-11 Vincent Y. F. Tan , Hamdi Joudeh

We consider the problem of modulation and estimation of a random parameter $U$ to be conveyed across a discrete memoryless channel. Upper and lower bounds are derived for the best achievable exponential decay rate of a general moment of the…

Information Theory · Computer Science 2016-11-17 Neri Merhav

The error exponent of fixed-length lossy source coding was established by Marton. Ahlswede showed that this exponent can be discontinuous at a rate $R$, depending on the probability distribution $P$ of the given information source and the…

Information Theory · Computer Science 2023-04-25 Yutaka Jitsumatsu

Consider the transmission of a polar code of block length $N$ and rate $R$ over a binary memoryless symmetric channel $W$ and let $P_e$ be the block error probability under successive cancellation decoding. In this paper, we develop new…

Information Theory · Computer Science 2016-08-05 Marco Mondelli , S. Hamed Hassani , Rüdiger Urbanke

We study the following semi-deterministic setting of the joint source-channel coding problem: a deterministic source sequence (a.k.a. individual sequence) is transmitted via a memoryless channel, using delay-limited encoder and decoder,…

Information Theory · Computer Science 2021-09-29 Neri Merhav

In this work, we consider decoupling a bipartite quantum state via a general quantum channel. We propose a joint state-channel decoupling approach to obtain a one-shot error exponent bound without smoothing, in which trace distance is used…

Quantum Physics · Physics 2024-09-24 Hao-Chung Cheng , Frédéric Dupuis , Li Gao

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…

Computer Vision and Pattern Recognition · Computer Science 2022-05-27 Jun Wang , Sixian Wang , Jincheng Dai , Zhongwei Si , Dekun Zhou , Kai Niu

Exponential error bounds achievable by universal coding and decoding are derived for frame-asynchronous discrete memoryless %asynchronous multiple access channels with two senders, via the method of subtypes, a refinement of the method of…

Information Theory · Computer Science 2020-02-04 Lóránt Farkas , Tamás Kói

This paper investigates achievable information rates and error exponents of mismatched decoding when the channel belongs to the class of channels that are close to the decoding metric in terms of relative entropy. For both discrete- and…

Information Theory · Computer Science 2025-05-28 Priyanka Patel , Francesc Molina , Albert Guillén i Fàbregas

The joint source-channel coding (JSCC) framework leverages deep learning to learn from data the best codes for source and channel coding. When the output signal, rather than being binary, is directly mapped onto the IQ domain…

Machine Learning · Computer Science 2024-06-07 Junli Fang , João F. C. Mota , Baoshan Lu , Weicheng Zhang , Xuemin Hong