Lattice Gaussian Sampling by Markov Chain Monte Carlo: Bounded Distance Decoding and Trapdoor Sampling

DOI10.1109/TIT.2019.2901497zbMath1432.94061arXiv1704.02673OpenAlexW2883749581WikidataQ128315159 ScholiaQ128315159MaRDI QIDQ5224020

Cong Ling, Zheng Wang

Publication date: 19 July 2019

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1704.02673

zbMATH Keywords

complexityspectral gapconvergence rateparallel implementationrejection samplingdecoding radiustrapdoor samplingindependent Metropolis-Hastings-Klein (MHK) algorithmindependent multiple-try Metropolis-Klein (MTMK) algorithmMarkov chain Monte Carlo (MCMC)-based sampling techniquePeikert's algorithmperformance of bounded distance decoding (BDD) using MCMCsampling from the lattice Gaussian distribution

Mathematics Subject Classification ID

Detection theory in information and communication theory (94A13) Sampling theory in information and communication theory (94A20) Source coding (94A29)

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