Zheng Wang (王 正) |
2010.12 - 2015.05: Ph.D., Imperial College London, UK, Supervisor: Prof. Cong Ling
2009.09 - 2010.09: M.S., University of Manchester, UK, Supervisor: Prof. Patrick Gaydecki
2005.09 - 2009.06: B.S., Nanjing University of Aeronautics and Astronautics, China
2021.05 - present: Associate Professor, Southeast University, Nanjing, China
2017.09 - 2021.05: Assistant Professor & Associate Professor, Nanjing University of Aeronautics and Astronautics, China
2016.06 - 2017.08: Senior Engineer, Huawei Technologies Company, Shanghai, China
2015.05 - 2016.06: Post-doctoral, Imperial College London, UK
Research Background:
Research Framework:
Research Methodology:
Group Photo:
Journal Articles:
[1] Z. Wang* and C. Ling, “Lattice Gaussian sampling by Markov chain Monte Carlo: Bounded distance decoding and trapdoor sampling, ” IEEE Transactions on Information Theory (TIT, 通信与信号处理领域至尊期刊), vol. 65, no.6, pp. 3630-3645, June, 2019. [Link] [PDF]
[2] Z. Wang* and C. Ling, “On the geometric ergodicity of Metropolis-Hastings algorithms for lattice Gaussian sampling,” IEEE Transactions on Information Theory (TIT, 通信与信号处理领域至尊期刊), vol. 64, no. 2, pp. 738-751, Feb, 2018. [Link] [PDF]
[3] Z. Wang*, Y. Huang and S. Lyu, “Lattice-Reduction-Aided Gibbs Algorithm for Lattice Gaussian Sampling: Convergence Enhancement and Decoding Optimization,” IEEE Transactions on Signal Processing (TSP, 通信与信号处理领域权威期刊), vol. 67, no. 16, pp. 4342-4356, Aug, 2019. [Link] [PDF]
[4] Z. Wang*, R. M. Gower, C. Zhang, S. Lyu, Y. Xia and Y. Huang, “A Statistical Linear Precoding Scheme Based On Random Iterative Method For Massive MIMO Systems,” IEEE Transactions on Wireless Communications (TWC, 通信与信号处理领域权威期刊), vol. 21, no. 12, pp. 10115-10129, Dec. 2022. [Link] [PDF]
[5] Z. Wang*, S. Lyu, L. Liu and Y. Xia, “Learning-Aided Markov Chain Monte Carlo Scheme for Spectrum Sensing in Cognitive Radio,” IEEE Transactions on Vehicular Technology (TVT, 通信与信号处理领域主流期刊), vol. 71, no.10, pp. 11301-11305, Oct. 2022. [Link] [PDF]
[6] Z. Wang*, R. M. Gower, Y. Xia, L. He and Y. Huang, “Randomized Iterative Methods for Low-Complexity Large-Scale MIMO Detection,” IEEE Transactions on Signal Processing (TSP, 通信与信号处理领域权威期刊), vol. 70, pp. 2934-2949, 2022. [Link] [PDF]
[7] Z. Wang*, “Markov chain Monte Carlo Methods for Lattice Gaussian Sampling: Convergence Analysis and Enhancement,” IEEE Transactions on Communications (TCOM, 通信与信号处理领域权威期刊), vol. 67, no. 16, pp. 67116724, Oct, 2019. [Link] [PDF]
[8] Z. Wang*, L. Liu and C. Ling, “Sliced Lattice Gaussian Sampling: Convergence Enhancement and Decoding Optimization,” IEEE Transactions on Communications (TCOM, 通信与信号处理领域权威期刊), vol. 69, no. 4, pp. 2599-2612, April 2021. [Link] [PDF]
[9] Z. Wang*, S. Lyu, Y. Xia and Q. Wu, “Expectation Propagation-based Sampling Decoding: Enhancement and Optimization,” IEEE Transactions on Signal Processing (TSP, 通信与信号处理领域权威期刊), vol. 69, pp. 195-209,2021. [Link] [PDF]
[10] Z. Wang*, Y. Xia, J. Li and Q. Wu, “A New Method of Integer Parameter Estimation in Linear Models with Applications to GNSS High Precision Positioning,” IEEE Transactions on Signal Processing (TSP, 通信与信号处理领域权威期刊), vol. 69, pp. 4567-4579, 2021. [Link] [PDF]
[11] Z. Wang*, S. Liu and C. Ling, “Decoding by sampling part II: Derandomization and soft-output decoding,” IEEE Transactions on Communications (TCOM, 通信与信号处理领域权威期刊), vol. 61, no. 11, pp. 4630-4639, Nov, 2013. [Link] [PDF]
[12] Z. Wang*, W. Xu, Y. Xia, Q. Shi and Y. Huang, “A New Randomized Iterative Detection Algorithm For Uplink Large-scale MIMO Systems,” IEEE Transactions on Communications (TCOM, 通信与信号处理领域权威期刊), vol. 71, no. 9, pp. 5093-5107, Sept, 2023. [Link] [PDF]
[13] Z. Wang*, J. Wang, Z. Gao, Y. Huang, D. W. K. Ng and L. Hanzo*, “Rapidly Converging Low-Complexity Iterative Transmit Precoders for Massive MIMO Downlink,” IEEE Transactions on Communications (TCOM, 通信与信号处理领域权威期刊), vol. 71, no. 12, pp. 7228-7243, Dec. 2023. [Link] [PDF]
[14] Z. Wang*, C. Ling, S. Jin, Y. Huang and F. Gao, “Probabilistic Searching For MIMO Detection Based On Lattice Gaussian Distribution,” IEEE Transactions on Communications (TCOM, 通信与信号处理领域权威期刊), vol. 72, no. 1, pp. 85-100, Jan. 2024. [Link] [PDF]
[15] Z. Wang*, Y. Xia, C. Ling and Y. Huang, “Randomized Iterative Sampling Decoding Algorithm For Large-Scale MIMO Detection,” IEEE Transactions on Signal Processing (TSP, 通信与信号处理领域权威期刊), vol. 72, pp. 580-593, 2024. [Link] [PDF]
[16] Z. Wang*, L. Liang, S. Lyu, Y. Xia, Y. Huang* and D. W. K. Ng, “Efficient Statistical Linear Precoding for Downlink Massive MIMO Systems,” IEEE Transactions on Wireless Communications (TWC, 通信与信号处理领域权威期刊), Early Access, July. 2024. [Link]
Conference Articles:
[1] Z. Wang* and C. Ling, “On the geometric ergodicity of Gibbs algorithm for lattice Gaussian sampling,” IEEE Information Theory Workshop (ITW, 信息论旗舰会议), pp. 269-273, Kaohsiung, Taiwan, Nev. 2017. [Link] [PDF]
[2] Z. Wang* and C. Ling, “Symmetric Metropolis-within-Gibbs algorithm for lattice Gaussian sampling,” IEEE Information Theory Workshop (ITW, 信息论旗舰会议), pp.394-398, Cambridge, UK, Sept, 2016. [Link] [PDF]
[3] Z. Wang* and C. Ling, “Further results on independent Metropolis-Hastings-Klein sampling,” Proc. IEEE International Symposium on Information Theory (ISIT, 信息论旗舰会议), pp. 1924-1928, Barcelona, Spain, Jun. 2016. [Link] [PDF]
[4] Z. Wang* and C. Ling, “Independent Metropolis-Hastings-Klein algorithm for lattice Gaussian sampling,” Proc. IEEE International Symposium on Information Theory (ISIT, 信息论旗舰会议), pp.2470-2474, Hong Kong, China, Jun. 2015. [Link] [PDF]
[5] Z. Wang* G. Hanrot and C. Ling, “Markov chain Monte Carlo algorithms for lattice Gaussian sampling,” Proc. IEEE International Symposium on Information Theory (ISIT, 信息论旗舰会议), pp. 1489-1493, Honolulu, USA, Jun. 2014. [Link] [PDF]
[6] Z. Wang* and C. Ling, “Derandomized sampling algorithm for lattice decoding,” IEEE Information Theory Workshop (ITW, 信息论旗舰会议), pp. 222-226, Lausanne, Swiss, Sep. 2012. [Link] [PDF]
[7] Z. Wang* and C. Ling, “Slice Sampling for lattice Gaussian distribution,” Proc. IEEE International Symposium on Information Theory (ISIT, 信息论旗舰会议), Paris, France, July, 2019. [Link] [PDF]
[8] Z. Wang*, Y. Xia, S. Lyu and C. Ling, “Reinforcement Learning-Aided Markov Chain Monte Carlo For Lattice Gaussian Sampling,” IEEE Information Theory Workshop (ITW, 信息论旗舰会议), pp.1-5, Oct., 2021. [Link] [PDF]
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