Slice Sampling for Lattice Gaussian Distribution
Sampling from the lattice Gaussian distribution has emerged as a key problem in coding and cryptography. In this paper, the slice sampling from Markov chain Monte Carlo (MCMC) is adopted to lattice Gaussian sampling. Firstly, the slice-based sampling algorithm is proposed to sample from lattice Gaus...
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| Vydáno v: | Proceedings / IEEE International Symposium on Information Theory s. 2589 - 2593 |
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01.07.2019
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| ISSN: | 2157-8117 |
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| Abstract | Sampling from the lattice Gaussian distribution has emerged as a key problem in coding and cryptography. In this paper, the slice sampling from Markov chain Monte Carlo (MCMC) is adopted to lattice Gaussian sampling. Firstly, the slice-based sampling algorithm is proposed to sample from lattice Gaussian distribution. Then, we demonstrate that the Markov chain arising from it is uniformly ergodic, namely, it converges exponentially fast to the stationary distribution. Moveover, the convergence rate of the underlying Markov chain is investigated, and we show the proposed slice sampling algorithm entails a better convergence performance than the independent Metropolis-Hastings-Klein (IMHK) sampling algorithm. Finally, simulation results based on MIMO detection are presented to confirm the performance gain by convergence enhancement. |
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| AbstractList | Sampling from the lattice Gaussian distribution has emerged as a key problem in coding and cryptography. In this paper, the slice sampling from Markov chain Monte Carlo (MCMC) is adopted to lattice Gaussian sampling. Firstly, the slice-based sampling algorithm is proposed to sample from lattice Gaussian distribution. Then, we demonstrate that the Markov chain arising from it is uniformly ergodic, namely, it converges exponentially fast to the stationary distribution. Moveover, the convergence rate of the underlying Markov chain is investigated, and we show the proposed slice sampling algorithm entails a better convergence performance than the independent Metropolis-Hastings-Klein (IMHK) sampling algorithm. Finally, simulation results based on MIMO detection are presented to confirm the performance gain by convergence enhancement. |
| Author | Ling, Cong Wang, Zheng |
| Author_xml | – sequence: 1 givenname: Zheng surname: Wang fullname: Wang, Zheng organization: College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210000, China – sequence: 2 givenname: Cong surname: Ling fullname: Ling, Cong organization: Department of EEE, Imperial College London, London, SW7 2AZ, United Kingdom |
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| Snippet | Sampling from the lattice Gaussian distribution has emerged as a key problem in coding and cryptography. In this paper, the slice sampling from Markov chain... |
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| SubjectTerms | Convergence Encoding Gaussian distribution Gold lattice coding and decoding Lattice Gaussian sampling Lattices M-CMC methods Markov processes slice sampling Zinc |
| Title | Slice Sampling for Lattice Gaussian Distribution |
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