Reinforcement Learning-Aided Markov Chain Monte Carlo For Lattice Gaussian Sampling

Sampling from the lattice Gaussian distribution has emerged as a key problem in coding, decoding and cryptography. In this paper, the Gibbs sampling from Markov chain Monte Carlo (MCMC) methods is investigated for lattice Gaussian sampling. Firstly, the error function of random scan Gibbs sampling i...

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Vydané v:	2021 IEEE Information Theory Workshop (ITW) s. 1 - 5
Hlavní autori:	Wang, Zheng, Xia, Yili, Lyu, Shanxiang, Ling, Cong
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 17.10.2021
Predmet:	Gaussian distribution lattice coding and decoding Lattice Gaussian sampling Lattices Markov chain Monte Carlo Markov processes MIMO detection Monte Carlo methods Performance gain Reinforcement learning Simulation
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