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Related papers: Building Blocks of Physical-layer Network Coding

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We review a class of methods that can be collected under the name nonlinear transform coding (NTC), which over the past few years have become competitive with the best linear transform codecs for images, and have superseded them in terms of…

Convolution is the main building block of convolutional neural networks (CNN). We observe that an optimized CNN often has highly correlated filters as the number of channels increases with depth, reducing the expressive power of feature…

Computer Vision and Pattern Recognition · Computer Science 2020-09-28 Xudong Wang , Stella X. Yu

A new class of spatially-coupled turbo-like codes (SC-TCs), dubbed generalized spatially coupled parallel concatenated codes (GSC-PCCs), is introduced. These codes are constructed by applying spatial coupling on parallel concatenated codes…

Information Theory · Computer Science 2022-02-25 Min Qiu , Xiaowei Wu , Jinhong Yuan , Alexandre Graell i Amat

In optical-processing-enabled network, transitional lightpaths crossing the same node could be optically encoded to each other to achieve greater spectral efficiency. In this context, we present a new research problem, entitled, routing,…

Networking and Internet Architecture · Computer Science 2022-04-27 Dao Thanh Hai

In this paper we design network coding schemes for Differential Chaos Shift Keying (DCSK) modulation. In this work, non-coherent chaos-based communication system is used due to its simplicity and robustness to multipath propagation effects,…

Information Theory · Computer Science 2015-05-13 Georges Kaddoum , Mohammed El-Hajjar

Recently years, the attempts on distilling mobile data into useful knowledge has been led to the deployment of machine learning algorithms at the network edge. Principal component analysis (PCA) is a classic technique for extracting the…

Information Theory · Computer Science 2022-04-04 Zezhong Zhang , Guangxu Zhu , Rui Wang , Vincent K. N. Lau , Kaibin Huang

Finding dense components in graphs is of great importance in analyzing the structure of networks. Popular and computationally feasible frameworks for discovering dense subgraphs are core and truss decompositions. Recently, Sariyuce et al.…

Social and Information Networks · Computer Science 2021-11-05 Fatemeh Esfahani , Venkatesh Srinivasan , Alex Thomo , Kui Wu

In this paper, we propose a hybrid nano communication (HNC) system that integrates three possible modes of nano communications: terahertz communication (TC), molecular communication (MC), and neural communication (NC). The paper provides…

Information Theory · Computer Science 2019-09-13 S. M. Riazul Islam , M. Jalil Piran , Anish P. Shreesta , Farman Ali , Asif Iqbal , Kyung-Sup Kwak

Ultra-reliable Point-to-Multipoint (PtM) communications are expected to become pivotal in networks offering future dependable services for smart cities. In this regard, sparse Random Linear Network Coding (RLNC) techniques have been widely…

Information Theory · Computer Science 2019-01-30 Suzie Brown , Oliver Johnson , Andrea Tassi

Network coding has been successfully used in the past for efficient broadcasting in wireless multi-hop networks. Two coding approaches are suitable for mobile networks; Random Linear Network Coding (RLNC) and XOR-based coding. In this work,…

Networking and Internet Architecture · Computer Science 2014-11-18 Nikolaos Papanikos , Evangelos Papapetrou

Constant dimension codes (CDCs) have become an important object in coding theory due to their application in random network coding. The multilevel construction is one of the most effective ways to construct constant dimension codes. The…

Information Theory · Computer Science 2025-11-03 Dengming Xu , Mengmeng LI

This paper presents novel techniques for improving the error correction performance and reducing the complexity of coarsely quantized 5G-LDPC decoders. The proposed decoder design supports arbitrary message-passing schedules on a…

Information Theory · Computer Science 2025-08-19 Philipp Mohr , Gerhard Bauch

Reliable communication over noisy channels requires the design of specialized error-correcting codes (ECCs) tailored to specific system requirements. Recently, neural network-based decoders have emerged as promising tools for enhancing ECC…

Information Theory · Computer Science 2025-12-01 Anastasiia Kurmukova , Selim F. Yilmaz , Emre Ozfatura , Deniz Gunduz

Based on the classical Degree Corrected Stochastic Blockmodel (DCSBM) model for network community detection problem, we propose two novel approaches: principal component clustering (PCC) and normalized principal component clustering (NPCC).…

Machine Learning · Statistics 2020-11-11 Huan Qing , Jingli Wang

In this work, we propose a fully differentiable graph neural network (GNN)-based architecture for channel decoding and showcase a competitive decoding performance for various coding schemes, such as low-density parity-check (LDPC) and BCH…

Information Theory · Computer Science 2022-10-13 Sebastian Cammerer , Jakob Hoydis , Fayçal Aït Aoudia , Alexander Keller

Sharding is the prevalent approach to breaking the trilemma of simultaneously achieving decentralization, security, and scalability in traditional blockchain systems, which are implemented as replicated state machines relying on atomic…

Cryptography and Security · Computer Science 2021-03-01 Yizhong Liu , Jianwei Liu , Marcos Antonio Vaz Salles , Zongyang Zhang , Tong Li , Bin Hu , Fritz Henglein , Rongxing Lu

This paper considers a data collection network consisting of uncoordinated, heterogeneous, and possibly mobile devices. These devices use medium and short-range radio technologies, which require multi-hop communication to deliver data to…

Networking and Internet Architecture · Computer Science 2018-12-31 Cédric Adjih , Michel Kieffer , Claudio Greco

In fault-tolerant quantum computing, a large number of physical qubits are required to construct a single logical qubit, and a single quantum node may be able to hold only a small number of logical qubits. In such a case, the idea of…

Quantum Physics · Physics 2026-01-15 Soshun Naito , Yasunari Suzuki , Yuuki Tokunaga

Spectral graph theory-based methods represent an important class of tools for studying the structure of networks. Spectral methods are based on a first-order Markov chain derived from a random walk on the graph and thus they cannot take…

Social and Information Networks · Computer Science 2018-01-08 Austin R. Benson , David F. Gleich , Jure Leskovec

The advent of network coding presents promising opportunities in many areas of communication and networking. It has been recently shown that network coding technique can significantly increase the overall throughput of wireless networks by…

Information Theory · Computer Science 2007-07-13 Salim Y. El Rouayheb , Mohammad Asad R. Chaudhry , Alex Sprintson
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