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This paper studies random-coding error exponents of randomised list decoding, in which the decoder randomly selects $L$ messages with probabilities proportional to the decoding metric of the codewords. The exponents (or bounds) are given…

Information Theory · Computer Science 2026-01-15 Henrique K. Miyamoto , Sheng Yang

Exponential error bounds for the finite-alphabet interference channel (IFC) with two transmitter-receiver pairs, are investigated under the random coding regime. Our focus is on optimum decoding, as opposed to heuristic decoding rules that…

Information Theory · Computer Science 2008-10-14 Raul Etkin , Neri Merhav , Erik Ordentlich

We present a theoretical method for a direct evaluation of the average and reliability error exponents in low-density parity-check error-correcting codes using methods of statistical physics. Results for the binary symmetric channel (BSC)…

Disordered Systems and Neural Networks · Physics 2016-08-31 N. S. Skantzos , J. van Mourik , D. Saad , Y. Kabashima

Capacity formulas and random-coding exponents are derived for a generalized family of Gel'fand-Pinsker coding problems. These exponents yield asymptotic upper bounds on the achievable log probability of error. In our model, information is…

Information Theory · Computer Science 2007-07-13 Pierre Moulin , Ying Wang

We consider the problem of slotted asynchronous coded communication, where in each time frame (slot), the transmitter is either silent or transmits a codeword from a given (randomly selected) codebook. The task of the decoder is to decide…

Information Theory · Computer Science 2013-08-22 Neri Merhav

We derive a sphere-packing error exponent for coded transmission over discrete memoryless channels with a fixed decoding metric. By studying the error probability of the code over an auxiliary channel, we find a lower bound to the…

Information Theory · Computer Science 2022-12-29 Ehsan Asadi Kangarshahi , Albert Guillén i Fàbregas

In the literature there exists analytical expressions for the probability of a receiver decoding a transmitted source message that has been encoded using random linear network coding. In this work, we look into the probability that the…

Information Theory · Computer Science 2022-03-08 Jessica Claridge , Ioannis Chatzigeorgiou

This paper studies the random-coding exponent of joint source-channel coding for a scheme where source messages are assigned to disjoint subsets (referred to as classes), and codewords are independently generated according to a distribution…

Information Theory · Computer Science 2014-02-19 Adrià Tauste Campo , Gonzalo Vazquez-Vilar , Albert Guillén i Fàbregas , Tobias Koch , Alfonso Martinez

We introduce two notions of discrepancy between binary vectors, which are not metric functions in general but nonetheless capture the mathematical structure of the binary asymmetric channel. In turn, these lead to two new fundamental…

Information Theory · Computer Science 2022-01-19 Giuseppe Cotardo , Alberto Ravagnani

We consider the discrete memoryless degraded broadcast channels with feedback. We prove that the error probability of decoding tends to one exponentially for rates outside the capacity region and derive an explicit lower bound of this…

Information Theory · Computer Science 2015-04-24 Yasutada Oohama

The security level of the achievability scheme for Wyner's wiretap channel model is examined from the perspective of the probability of correct decoding, $P_c$, at the wiretap channel decoder. In particular, for finite-alphabet memoryless…

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

We consider the discrete memoryless degraded broadcast channels. We prove that the error probability of decoding tends to one exponentially for rates outside the capacity region and derive an explicit lower bound of this exponent function.…

Information Theory · Computer Science 2015-04-23 Yasutada Oohama

The binary asymmetric channel is a model for practical communication systems where the error probabilities for symbol transitions $0\rightarrow 1$ and $1\rightarrow0$ differ substantially. In this paper, we introduce the notion of…

Information Theory · Computer Science 2026-04-10 Shukai Wang , Cuiling Fan , Chunming Tang , Zhengchun Zhou

The error exponent of the typical random code is defined as the asymptotic normalized expectation of the logarithm of the probability of error, as opposed to the traditional definition of the random coding exponent as the normalized…

Information Theory · Computer Science 2018-12-18 Neri Merhav

We consider communication over binary-input memoryless output-symmetric channels using low-density parity-check codes and message-passing decoding. The asymptotic (in the length) performance of such a combination for a fixed number of…

Information Theory · Computer Science 2008-02-12 Satish Babu Korada , Ruediger Urbanke

Semantic encoders and decoders for digital semantic communication (SC) often struggle to adapt to variations in unpredictable channel environments and diverse system designs. To address these challenges, this paper proposes a novel…

Signal Processing · Electrical Eng. & Systems 2025-03-20 Yongjeong Oh , Joohyuk Park , Jinho Choi , Jihong Park , Yo-Seb Jeon

We consider the state dependent channels with full state information with at the sender. For this state dependent channel, the channel capacity was determined by Gel'fand and Pinsker. In this paper, we study the correct probability of…

Information Theory · Computer Science 2020-08-11 Yasutada Oohama

Sparse random linear network coding (SRLNC) used as a class of erasure codes to ensure the reliability of multicast communications has been widely investigated. However, an exact expression for the decoding success probability of SRLNC is…

Information Theory · Computer Science 2021-08-27 WenLin Chen , Fang Lu , Yan Dong

This paper studies the concentration properties of random codes. Specifically, we show that, for discrete memoryless channels, the error exponent of a randomly generated code with pairwise-independent codewords converges in probability to…

Information Theory · Computer Science 2022-03-16 Lan V. Truong , Giuseppe Cocco , Josep Font-Segura , Albert Guillén i Fàbregas

This paper investigates the error probability of a stochastic decision and the way in which it differs from the error probability of an optimal decision, i.e., the maximum a posteriori decision. This paper calls attention to the fact that…

Information Theory · Computer Science 2017-05-01 Jun Muramatsu , Shigeki Miyake