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Mismatch capacity characterizes the highest information rate for a channel under a prescribed decoding metric, and is thus a highly relevant fundamental performance metric when dealing with many practically important communication…

Information Theory · Computer Science 2022-08-17 Wenhao Ye , Huihui Wu , Shitong Wu , Yizhu Wang , Wenyi Zhang , Hao Wu , Bo Bai

The mismatch capacity characterizes the highest information rate of the channel under a prescribed decoding metric and serves as a critical performance indicator in numerous practical communication scenarios. Compared to the commonly used…

Information Theory · Computer Science 2025-07-29 Shitong Wu , Wenhao Ye , Xinwei Li , Lingyi Chen , Wenyi Zhang , Huihui Wu , Hao Wu

Reliable communication over a discrete memoryless channel with the help of a relay has aroused interest due to its widespread applications in practical scenarios. By considering the system with a mismatched decoder, previous works have…

Information Theory · Computer Science 2024-10-16 Xinwei Li , Lingyi Chen , Shitong Wu , Huihui Wu , Hao Wu , Wenyi Zhang

We derive a single-letter upper bound to the mismatched-decoding capacity for discrete memoryless channels. The bound is expressed as the mutual information of a transformation of the channel, such that a maximum-likelihood decoding error…

Information Theory · Computer Science 2021-02-16 Ehsan Asadi Kangarshahi , Albert Guillén i Fàbregas

The problem of mismatched decoding for discrete memoryless channels is addressed. A mismatched cognitive multiple-access channel is introduced, and an inner bound on its capacity region is derived using two alternative encoding methods:…

Information Theory · Computer Science 2013-05-03 Anelia Somekh-Baruch

We study the half-duplex multiple-relay channel (HD-MRC) where every node can either transmit or listen but cannot do both at the same time. We obtain a capacity upper bound based on a max-flow min-cut argument and achievable transmission…

Information Theory · Computer Science 2012-12-04 Lawrence Ong , Mehul Motani , Sarah J. Johnson

The common approach of designing a communication device is to maximize a well-defined objective function, e.g., the channel capacity and the cut-off rate. We propose easy-to-implement solutions for Gaussian channels that approximate the…

Information Theory · Computer Science 2016-03-24 Qian Yu

The problem of computing a linear combination of sources over a multiple access channel is studied. Inner and outer bounds on the optimal tradeoff between the communication rates are established when encoding is restricted to random…

Information Theory · Computer Science 2018-10-30 Pinar Sen , Sung Hoon Lim , Young-Han Kim

The important problem of weighted sum rate maximization (WSRM) in a multicellular environment is intrinsically sensitive to channel estimation errors. In this paper, we study ways to maximize the weighted sum rate in a linearly precoded…

Information Theory · Computer Science 2013-10-21 Muhammad Fainan Hanif , Le-Nam Tran , Antti Tölli , Markku Juntti , Savo Glisic

In this paper, we propose a novel algorithm to maximize the sum rate in interference-limited scenarios where each user decodes its own message with the presence of unknown interferences and noise considering the…

Information Theory · Computer Science 2015-03-23 Hussein Al-Shatri , Xiang Li , Rakash SivaSiva Ganesan , Anja Klein , Tobias Weber

We introduce a new analysis technique to derive a single-letter upper bound on the mismatch capacity of a stationary, single-user, memoryless channel with a decoding metric $q$. Our bound is obtained by considering a multicast transmission…

Information Theory · Computer Science 2021-03-29 Anelia Somekh-Baruch

We take a new perspective on the weighted sum-rate maximization in multiple-input multiple-output (MIMO) interference networks, by formulating an equivalent max-min problem. This seemingly trivial reformulation has significant implications:…

Information Theory · Computer Science 2013-09-17 Lijun Chen , Seungil You

This paper studies multiuser random coding techniques for channel coding with a given (possibly suboptimal) decoding rule. For the mismatched discrete memoryless multiple-access channel, an error exponent is obtained that is tight with…

Information Theory · Computer Science 2016-11-18 Jonathan Scarlett , Alfonso Martinez , Albert Guillén i Fàbregas

MIMO interference network optimization is important for increasingly crowded wireless communication networks. We provide a new algorithm, named Dual Link algorithm, for the classic problem of weighted sum-rate maximization for MIMO…

Information Theory · Computer Science 2016-04-05 Xing Li , Seungil You , Lijun Chen , An Liu , Youjian , Liu

Linear programming (LP) decoding approximates maximum-likelihood (ML) decoding of a linear block code by relaxing the equivalent ML integer programming (IP) problem into a more easily solved LP problem. The LP problem is defined by a set of…

Information Theory · Computer Science 2013-01-01 Xiaojie Zhang , Paul H. Siegel

This paper considers coordinated linear precoding for rate optimization in downlink multicell, multiuser orthogonal frequency- division multiple access networks. We focus on two different design criteria. In the first, the weighted sum-rate…

Information Theory · Computer Science 2015-06-17 Mirza Golam Kibria , Hidekazu Murata

This paper studies the mismatched decoding problem for binary-input discrete memoryless channels. An example is provided for which an achievable rate based on superposition coding exceeds the LM rate (Hui, 1983; Csisz\'ar-K\"orner, 1981),…

Information Theory · Computer Science 2015-08-11 Jonathan Scarlett , Anelia Somekh-Baruch , Alfonso Martinez , Albert Guillén i Fàbregas

In this paper, a novel decoding algorithm for low-density parity-check (LDPC) codes based on convex optimization is presented. The decoding algorithm, called interior point decoding, is designed for linear vector channels. The linear vector…

Information Theory · Computer Science 2009-11-13 Tadashi Wadayama

Factor analysis, a classical multivariate statistical technique is popularly used as a fundamental tool for dimensionality reduction in statistics, econometrics and data science. Estimation is often carried out via the Maximum Likelihood…

Optimization and Control · Mathematics 2018-01-19 Koulik Khamaru , Rahul Mazumder

We study the problem of computing the capacity of a discrete memoryless channel under uncertainty affecting the channel law matrix, and possibly with a constraint on the average cost of the input distribution. The problem has been…

Information Theory · Computer Science 2018-05-28 Krzysztof Postek , Aharon Ben-Tal
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