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A Unified Discretization Approach to Compute–Forward: From Discrete to Continuous Inputs

Publications associées (52)

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This paper considers the problem of distributed lossy compression where the goal is to recover one or more linear combinations of the sources at the decoder, subject to distortion constraints. For certain configurations, it is known that codes with algebra ...

2023

Compute-Forward for DMCs: Simultaneous Decoding of Multiple Combinations

Michael Christoph Gastpar, Sung Hoon Lim, Adriano Pastore, Chen Feng

Algebraic network information theory is an emerging facet of network information theory, studying the achievable rates of random code ensembles that have algebraic structure, such as random linear codes. A distinguishing feature is that linear combinations ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Recursive Projection-Aggregation Decoding of Reed-Muller Codes

Emmanuel Abbé, Min Ye

We propose a new class of efficient decoding algorithms for Reed-Muller (RM) codes over binary-input memoryless channels. The algorithms are based on projecting the code on its cosets, recursively decoding the projected codes (which are lower-order RM code ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Compute–Forward Multiple Access (CFMA): Practical Implementations

Michael Christoph Gastpar, Sung Hoon Lim, Jingge Zhu, Erixhen Sula, Adriano Pastore

We present a practical strategy that aims to attain rate points on the dominant face of the multiple access channel capacity using a standard low complexity decoder. This technique is built upon recent theoretical developments of Zhu and Gastpar on compute ...

2019

In his landmark paper "A Mathematical Theory of Communication," the founding father of information theory and coding theory, Claude E. Shannon, established the largest rate at which reliable communication is possible and he revealed that the key to this re ...

EPFL2019

Universal Sparse Superposition Codes With Spatial Coupling and GAMP Decoding

Nicolas Macris, Jean François Emmanuel Barbier, Mohamad Baker Dia

Sparse superposition codes, or sparse regression codes, constitute a new class of codes, which was first introduced for communication over the additive white Gaussian noise (AWGN) channel. It has been shown that such codes are capacity-achieving over the A ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

Towards an Algebraic Network Information Theory: Distributed Lossy Computation of Linear Functions

Michael Christoph Gastpar, Sung Hoon Lim, Adriano Pastore, Chen Feng

Consider the important special case of the K-user distributed source coding problem where the decoder only wishes to recover one or more linear combinations of the sources. The work of Körner and Marton demonstrated that, in some cases, the optimal rate re ...

2019

A Joint Typicality Approach to Compute–Forward

Michael Christoph Gastpar, Sung Hoon Lim, Adriano Pastore, Chen Feng

This paper presents a joint typicality framework for encoding and decoding nested linear codes in multi-user networks. This framework provides a new perspective on compute–forward within the context of discrete memoryless networks. In particular, it establ ...

2018

Almost Optimal Scaling of Reed-Muller Codes on BEC and BSC Channels

Rüdiger Urbanke, Seyed Hamed Hassani, Shrinivas Kudekar, Yury Polyanskiy

Consider a binary linear code of length N, minimum distance d(min), transmission over the binary erasure channel with parameter 0 < epsilon < 1 or the binary symmetric channel with parameter 0 < epsilon < 1/2, and block-MAP decoding. It was shown by Tillic ...

IEEE2018

Coding for Communications and Secrecy

Mani Bastaniparizi

Shannon, in his landmark 1948 paper, developed a framework for characterizing the fundamental limits of information transmission. Among other results, he showed that reliable communication over a channel is possible at any rate below its capacity. In 2008, ...

EPFL2017