[1] 国家青年自然科学基金，2019-2021(A类上会)
[2] 江苏省青年自然科学基金，2018-2020
[3] 东南大学无线通信国家重点实验室开放课题基金，2018-2019
[4] 南航电磁频谱工信部重点实验室开放课题基金，2018-2019
[5] 中国航天科工集团八五一一研究所项目2018-2019（主持）
[6] 电科集团三十六研究所项目2019-2021（主持）
[7] 电子信息系统复杂电磁环境效应国家重点实验室课题项目，2017-2018（主持）
[8] 电科集团十四所项目，2019-2021（参与）
[9] 电科集团二十八所项目，2019-2021（参与）
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第一作者代表论文

[J1] Zheng Wang* and Cong Ling, “Lattice Gaussian sampling by Markov chain Monte Carlo: Bounded distance decoding and trapdoor sampling, ” IEEE Transactions on Information Theory, vol. 65, no. 6, pp. 3630-3645, June, 2019.

[J2] Zheng Wang* and Cong Ling, “On the geometric ergodicity of Metropolis-Hastings algorithms for lattice Gaussian sampling,” IEEE Transactions on Information Theory, vol. 64, no. 2, pp. 738-751, Feb, 2018.

[J3] Zheng Wang*, Shuiyin Liu and Cong Ling, “Decoding by sampling part II: Derandomization and soft-output decoding,” IEEE Transactions on Communications, vol. 61, no. 11, pp. 4630-4639, Nov, 2013.

[J4] Zheng Wang*,Yang Huang and Shanxiang Lyu, “Lattice-Reduction-Aided Gibbs Algorithm for Lattice Gaussian Sampling: Convergence Enhancement and Decoding Optimization,” IEEE Transactions on Signal Processing, vol. 67, no. 16, pp. 4342-4356, Aug, 2019.

[J5] Zheng Wang*,“Markov chain Monte Carlo Methods For Lattice Gaussian Sampling: Convergence Analysis and Enhancement,” IEEE Transactions on Communications, 2019.

[J6] Zheng Wang*, Cong Ling and Shi Jin, “Deterministic Sampling Decoding: Where Sphere Decoding Meets Lattice Gaussian Distribution,” submitted to IEEE Transactions on Information Theory, 2019.

[Online]Available: https://arxiv.org/abs/1907.09119.

[C1] Zheng Wang* and Cong Ling, “On the geometric ergodicity of Gibbs algorithm for lattice Gaussian sampling,” in Proc. IEEE Information Theory Workshop, ITW, pp. 269-273, Kaohsiung, Taiwan, Nev. 2017.

[C2] Zheng Wang* and Cong Ling, “Symmetric Metropolis-within-Gibbs algorithm for lattice Gaussian sampling,” in Proc. IEEE Information Theory Workshop, ITW, pp.394-398, Cambridge, UK, Sept, 2016.

[C3] Zheng Wang* and Cong Ling, “Further results on independent Metropolis-Hastings-Klein sampling,” in Proc. IEEE International Symposium on Information Theory, ISIT, pp. 1924-1928, Barcelona, Spain, Jun. 2016.

[C4] Zheng Wang* and Cong Ling, “Independent Metropolis-Hastings-Klein algorithm for lattice Gaussian sampling,” in Proc. IEEE International Symposium on Information Theory, ISIT, pp.2470-2474, Hong Kong, China, Jun. 2015.

[C5] Zheng Wang*, Guillaume Hanrot and Cong Ling, “Markov chain Monte Carlo algorithms for lattice Gaussian sampling,” in Proc. IEEE International Symposium on Information Theory, ISIT, pp. 1489-1493, Honolulu, USA, Jun. 2014.

[C6] Zheng Wang* and Cong Ling, “Derandomized sampling algorithm for lattice decoding,” in Proc. IEEE Information Theory Workshop, ITW, pp. 222-226, Lausanne, Swiss, Sep. 2012.

[C7] Zheng Wang* and Cong Ling, “Slice Sampling for lattice Gaussian distribution,” in Proc. IEEE International Symposium on Information Theory, ISIT, Paris, France, July, 2019.

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