Research
I am interested in Wireless Communication, Iterative Signal Processing, Message Passing Algorithm, MIMO, Multi-user Detection, Modern Channel Coding and Information Theory. Please feel free to drop me an email, if you
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□ One paper has been accepted by IEEE TIT.
In this work, we propose a new memory AMP (MAMP), which
In other words, MAMP inherits the strengths of AMP and OAMP/VAMP such as low complexity, Bayes optimality, and applicability to unitarily-invariant matrices, while avoiding the weaknesses of AMP (e.g. limited to IID matrices) and OAMP/VAMP (e.g. needs high-complexity LMMSE).
□ One paper has been accepted by IEEE TSP.
□ One paper has been accepted by IEEE TCom.
□ Three papers have been accepted by IEEE ISIT 2022.
□ L. Liu, S. Huang, and B. M. Kurkoski, "Sufficient statistic memory AMP," arXiv preprint: arXiv:2112.15327, Jan. 2022. (submitted to IEEE Transactions on Information Theory) [Matlab][Slides]
A distinguished feature of the AMP-type algorithms is that their dynamics can be rigorously described by state evolution. However, state evolution does not necessarily guarantee the convergence of iterative algorithms. To solve the convergence problem of AMP-type algorithms in principle, this paper proposes a memory AMP (MAMP) under a sufficient statistic condition, named sufficient statistic MAMP (SS-MAMP).
□ L. Liu, S. Liang, and L. Ping, "Capacity optimality of OAMP: Beyond IID sensing matrices and Gaussian signaling," arXiv preprint: arXiv:2108.08503, Aug. 2021. [Matlab][Slides]
In this work, we focus on the fundamental open problem: How to achieve the information-theoretic limit (i.e. constrained capacity) of a large linear system with a non-IID sensing (i.e., right-unitarily-invariant) matrix and non-Gaussian signaling? As a result, a capacity-achieving coded OAMP is designed based on matched FEC coding.
Note: This work is an extension of our previous work "Capacity optimality of AMP in coded systems", which shows the capacity optimality of a coded AMP for IID sensing matrix. For non-IID sensing matrices, AMP does not work well. This work is also an extension of our previous work "Capacity-achieving MIMO-NOMA: Iterative LMMSE detection", which shows the Gaussian capacity-achieving of Turbo LMMSE with Gaussian signaling. However, for practical non-Gaussian signaling, Turbo is not capacity optimal anymore!
□ L. Liu, C. Liang, J. Ma, and L. Ping, "Capacity optimality of AMP in coded systems," IEEE Transactions on Information Theory, vol. 67, no. 7, 4929-4445, July 2021, arXiv preprint arXiv:1901.09559, 2019. [Matlab][Slides][Video]
In this work, we focus on the following fundamental open problem in random linear systems: How to design a low-complexity strategy to achieve the information-theoretic limit of a random linear system with non-Gaussian input distributions? As a result, a low-complexity capacity-achieving coded AMP is designed based on matched FEC coding. In addition, we show that the conventional Turbo method is sub-optimal for non-Gaussian signaling. Apart from that, particular irregular LDPC codes are designed for AMP to obtain capacity-approaching BER performances for various system loads and SNRs.
Note: This is an extension of our previous work "Capacity-achieving MIMO-NOMA: Iterative LMMSE detection", which shows the Gaussian capacity-achieving of Turbo LMMSE with Gaussian signaling. However, for non-Gaussian signaling, Turbo is not capacity optimal anymore!
□ S. Huang, L. Liu and B. M. Kurkoski, "Algebra of L-banded matrices," in IEEE Access, vol. 11, pp. 17658-17664, 2023.
□ M. Yue, L. Liu, and X. Yuan, "RIS-Aided Multiuser MIMO-OFDM with Linear Precoding and Iterative Detection: Analysis and Optimization," IEEE Transactions on Wireless Communications, Mar. 2023. (Accepted)
□ L. Liu, S. Huang, and B. M. Kurkoski, "Memory AMP," IEEE Transactions on Information Theory, vol. 68, no. 12, pp. 8015-8039, Dec. 2022. [Matlab][Slides][Video]
□ L. Liu, S. Huang, and B. M. Kurkoski, "Sufficient statistic memory AMP," arXiv preprint: arXiv:2112.15327, Jan. 2022. (submitted to IEEE Transactions on Information Theory)
□ L. Liu, Y. Cheng, S. Liang, J. H. Manton, and L. Ping, "On orthogonal approximate message passing," arXiv preprint: arXiv:2203.00224, March 2022.
□ F. Tian, L. Liu and X. Chen, "Generalized Memory Approximate Message Passing for Generalized Linear Model," in IEEE Transactions on Signal Processing, vol. 70, pp. 6404-6418, 2022. [Matlab]
□ Y. Chi, L. Liu*, G. Song, Y. Li, Y. L. Guan, and C. Yuen, ``Constrained capacity Optimal generalized multi-user MIMO: A theoretical and practical framework," IEEE Transactions on Communications, vol. 70, no. 12, pp. 8086-8104, Dec. 2022. [Slides]
□ F. Tian, X. Chen, L. Liu, D. W. K. Ng, "Massive unsourced random access over Rician fading channels: Design, analysis, and optimization," IEEE Internet of Things Journal, vol. 9, no. 18, pp. 17675-17688, 15 Sept. 2022.
□ L. Liu, C. Liang, J. Ma, and L. Ping, "Capacity optimality of AMP in coded systems," IEEE Transactions on Information Theory, vol. 67, no. 7, 4929-4445, July 2021, arXiv preprint arXiv:1901.09559, 2019. [Matlab][Slides][Video]
□ L. Liu, S. Liang, and L. Ping, "Capacity optimality of OAMP: Beyond IID sensing matrices and Gaussian signaling," arXiv preprint: arXiv:2108.08503, Aug. 2021. [Matlab] □ Y. Cheng, L. Liu, L. Ping, "Orthogonal AMP for massive access in channels with spatial and temporal correlations," in IEEE Journal on Selected Areas in Communications, vol. 39, no. 3, 726-740, March 2021.
□ M. Yue, L. Liu, and X. Yuan, "Practical RIS-Aided Coded Systems: Joint Precoding and Passive Beamforming," IEEE Wireless Communications Letters, vol. 10, no. 11, 2345-2349, 2021.
□ Y. Cheng, L. Liu, L. Ping, "An integral-based approach to orthogonal AMP," in IEEE Signal Processing Letters, vol. 28, 194-198, Dec. 2020.
□ Z. Zhang, Y. Li, C. Huang, Q. Guo, L. Liu, C. Yuen, and Y. L. Guan, "User activity detection and channel estimation for grant-gree random access in LEO satellite-enabled internet-of-things," IEEE Internet of Things Journal, vol. 7, no. 9, 8811-8825, Mar. 2020.
□ L. Liu, Y. Chi, C. Yuen, Y. L. Guan, and Y. Li, "Capacity-achieving MIMO-NOMA: Iterative LMMSE detection," IEEE Transactions on Signal Processing, vol. 67, no. 7, 1758 - 1773, April 2019. [C++] [Slides] [Highly-Cited Paper]
□ L. Liu, C. Yuen, Y. L. Guan, Y. Li, and C. Huang, "Gaussian message passing for overloaded massive MIMO-NOMA," IEEE Transactions on Wireless Communications, vol. 18, no. 1, 210 - 226, Jan. 2019. [Matlab] [Slides] [Highly-Cited Paper]
□ L. Liu, Y. Li, C. Huang, C. Yuen, and G. Y. Liang, "A new insight into GAMP and AMP," IEEE Transactions on Vehicular Technology, vol. 68, no. 8, pp. 8264-8269, Aug. 2019. [Matlab]
□ J. Ma, L. Liu*, X. Yuan, and L. Ping, "On orthogonal AMP in coded linear vector systems," IEEE Transactions on Wireless Communications, 18(12), 6487-6501, Oct. 2019.
□ C. Huang, L. Liu*, C. Yuen, and S. Sun, "Iterative channel estimation using LSE and sparse message passing for mmWave MIMO systems," IEEE Transactions on Signal Processing, vol. 67, no. 1, pp. 245 - 259, Jan. 2019. [Highly-Cited Paper]
□ Y. Hu, C. Liang, L. Liu*, C. Y, Y. Y, and L. Ping "Interleave-division multiple access in high rate applications," IEEE Communications Letter, vol. 8, no. 2, pp 476-479, April 2019.
□ Y. Chi, L. Liu, J. Guo, G. Song, C. Yuen, and Y. L. Guan, "Variable-rate coding with constant BER for NOMA via multilevel IRA coding," IEEE Transactions on Vehicular Technology, vol. 68, no. 5, 5149-5153, May 2019.
□ Z. Zhang, Y. Li, L. Liu, and W. Hou, "Fixed-symbol aided random access scheme for machine-to-machine communications," IEEE Access, vol. 7, 52913 - 52928, April, 2019.
□ Y. Chi, L. Liu, G. Song, C. Yuen, Y. L. Guan, and Y. Li, "Practical MIMO-NOMA: Low complexity and capacity-approaching solution," IEEE Transactions on Wireless Communications, vol. 17, no. 9, 6251-6264, Sept. 2018. [C++]
□ C. Huang, L. Liu, and C. Yuen, "Asymptotically optimal estimation algorithm for the sparse signal with arbitrary distributions," IEEE Transactions on Vehicular Technology, vol. 67, no. 10, 10070-10075, July 2018.
□ Y. Su, Y. Li, X. Wu, and L. Liu, "Outage performance for amplify-and-forward two-hop multiple-access channel," IET Communications, vol. 12, no. 2, 205-213, Feb. 2018.
□ L. Liu, Y. Liang, and Y. Li, "A new upper bound on the achievable rate of relay channel with MIP-QF strategy," IEEE Transactions on Vehicular Technology, vol. 66, no. 8, 6787-6800, Aug. 2017.
□ L. Liu, Y. Li , C. Yuen, Y. L. Guan, and Y. Sun, "Joint source-channel coding for asymmetric Slepian-Wolf multiple access relay channel," IEEE Wireless Communications Letters, vol. 6, no. 5, 642-645, Oct 2017.
□ L. Liu, C. Yuen, Y. L. Guan, Y. Li, and Y. Su, "Convergence analysis and assurance for Gaussian message passing iterative detector in massive MU-MIMO systems," IEEE Transactions on Wireless Communications, vol. 15, no. 9, 6487-6501, Sept. 2016. [matlab] [Slides]
□ L. Liu, Y. Li, Y. Su, and Y. Sun, "Quantize-and-forward strategy for interleave division multiple-access relay channel," IEEE Transactions on Vehicular Technology, vol. 65, no. 3, 1808-1814, Mar. 2016.
□ Y Su, Y Li, G Song, and L Liu, "Achievable rate regions of multi-way relay channel with direct links," IET Communications, 9 (7), 947-959, May 2015.
□ 苏玉萍， 李颖， 刘雷, "干扰受限的两跳多接入信道的中断概率分析," 电子学报, 43 (12), 2414-2420, Mar 2015.
□ L. Liu, S. Huang, and B. M. Kurkoski, "Sufficient statistic memory approximate message passing," Proc. 2022 IEEE Int. Symp. Inf. Theory, Espoo, Finland, July 2022. [Matlab][Slides]
□ L. Liu, S. Liang, and L. Ping, "Capacity optimality of OAMP in coded large unitarily invariant systems," Proc. 2022 IEEE Int. Symp. Inf. Theory, Espoo, Finland, July 2022. [Matlab]][Slides]
□ Y. Chi, L. Liu*, G. Song, Y. Li, Y. L. Guan, and C. Yuen, "Capacity optimal coded generalized MU-MIMO," Proc. 2022 IEEE Int. Symp. Inf. Theory, Espoo, Finland, July 2022. [Slides]
□ L. Liu, S. Huang, and B. M. Kurkoski, "Memory approximate message passing," Proc. 2021 IEEE Int. Symp. Inf. Theory, pp. 1379-1384, Melbourne, Australia, July 2021. [Matlab][Slides][Video]
□ L. Liu, C. Liang, J. Ma, and L. Ping, "Capacity optimality of AMP in coded systems," Proc. 2021 IEEE Int. Symp. Inf. Theory, pp. 1588-1593, Melbourne, Australia, July 2021. [Matlab][Slides][Video]
□ W. Li, L. Liu*, and B. M. Kurkoski, "Irregularly Clipped Sparse Regression Codes," IEEE ITW 2021, Oct. 2021.[Slides][Video]
□ F. Tian, X. Chen, L. Liu, D. W. K. Ng, "Design of massive unsourced random access over Rician channels," 2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Sept. 2021.
□ J. Ma, L. Liu*, Y. Xiao, and L. Ping, "Iterative detection in coded linear systems based on orthogonal AMP," IEEE ISTC, Hong Kong, Dec 2018. [Slides]
□ Y. Hu, C. Liang, L. Liu, C. Yan, Y. Yuan, and L. Ping, "Interleave division multiple access for high overloading applications," IEEE ISTC, Hong Kong, Dec 2018.
□ Z. Zhang, Y. Li, L. Liu, and H. Han, "Sparse message passing based preamble estimation for crowded M2M communications," IEEE ICC, USA, May 2018.
□ L. Liu, C. Huang, Y. Chi, C. Yuen, Y. L. Guan, and Y. Li, "Sparse vector recovery: Bernoulli-Gaussian message passing," IEEE Globecom, Singapore, Dec 2017. [Matlab][Slides]
□ Y. Chi, L. Liu, G. Song, C. Yuen, Y. L. Guan, and Y. Li, "Message passing in C-RAN: Joint user activity and signal detection," IEEE Globecom, Singapore, Dec 2017.
□ T. S. Abeywickrama, L. Liu, Y. Chi, and C. Yuen, "Over-the-air implementation of uplink NOMA," IEEE Globecom, Singapore, Dec 2017.
□ L. Liu, C. Yuen, Y. L. Guan, Y. Li, and C. Huang, "Gaussian message passing iterative detection for MIMO-NOMA systems with massive access," IEEE Globecom, Washington, DC, USA, Dec 2016. [Matlab] [Slides]
□ C. Huang, L. Liu, C. Yuen, and S. Sun, "A LSE and Sparse message passing-based channel estimation for mmWave MIMO systems," IEEE Globecom Workshops, Washington, DC, USA, Dec 2016.
□ L. Liu, C. Yuen, Y. L. Guan, and Y. Li, "Capacity-achieving iterative LMMSE detection for MIMO-NOMA systems," IEEE ICC, Kuala Lumpur, Malaysia, May 2016.[C++] [Slides]
□ L. Liu, C. Yuen, Y. L. Guan, Y. Li, and Y. Su, "A low-complexity Gaussian message passing iterative detector for massive MU-MIMO systems," IEEE ICICS, Singapore, Dec. 2015. [Matlab] [Slides]
□ Wencong Li and Lei Liu, "LMMSE Estimation", JAIST, Nov. 2020.
□ Feiyan Tian and Lei Liu, "LMMSE (FFT version)", ZJU & JAIST, Jan. 2021.
□ Wencong Li and, Lei Liu, "Bernoulli-Gaussian Signal Estimation", JAIST, Dec. 2020.
□ Feiyan Tian and Lei Liu, "Orthogonalization", ZJU & JAIST, Dec. 2020.
□ Feiyan Tian and Lei Liu, "Declipping via Erfc", ZJU & JAIST, Mar. 2021.
□ Xuehui Chen, Yuhao Chi and Lei Liu, "GAMP and State Evolution", XDU & ZJU, Mar. 2023.
□ Xuehui Chen, Yuhao Chi and Lei Liu, "GOAMP with Unitary Matrices", XDU & ZJU, Mar. 2023.
□ Shunqi Huang, Yuzhi Yang and Lei Liu, "LDPC Decoding", JAIST & ZJU, April 2023.
□ Lei Liu, “非正交多址接入系统的检测及量化算法研究,” Xidian University, Xi'an, Nov. 2016. (In Chinese)
□ Latex Mathematical Symbols, Comprehensive Latex Symbol List
▪ are interested in my research or my papers,
▪ want our simulation source codes,
▪ want to visit or join our group.
News:
□ One paper has been accepted by IEEE TIT.
- L. Liu, S. Huang, and B. M. Kurkoski, "Memory AMP," IEEE Transactions on Information Theory, vol. 68, no. 12, pp. 8015-8039, Dec. 2022. [Matlab][Slides][Video]
In this work, we propose a new memory AMP (MAMP), which
- has comparable complexity to AMP and much lower complexity than OAMP/VAMP, since a low-complexity memory matched filter (MF) is considered for interference suppression;
- converges to the same fixed point as that of OAMP/VAMP for all unitarily invariant matrices. That is, MAMP is Bayes-optimal if it has a unique fixed point.
In other words, MAMP inherits the strengths of AMP and OAMP/VAMP such as low complexity, Bayes optimality, and applicability to unitarily-invariant matrices, while avoiding the weaknesses of AMP (e.g. limited to IID matrices) and OAMP/VAMP (e.g. needs high-complexity LMMSE).
□ One paper has been accepted by IEEE TSP.
- F. Tian, L. Liu and X. Chen, "Generalized Memory Approximate Message Passing for Generalized Linear Model," in IEEE Transactions on Signal Processing, vol. 70, pp. 6404-6418, 2022. [Matlab]
□ One paper has been accepted by IEEE TCom.
- Y. Chi, L. Liu*, G. Song, Y. Li, Y. L. Guan, and C. Yuen, ``Constrained capacity Optimal generalized multi-user MIMO: A theoretical and practical framework," IEEE Transactions on Communications, vol. 70, no. 12, pp. 8086-8104, Dec. 2022. [Slides]
□ Three papers have been accepted by IEEE ISIT 2022.
- L. Liu, S. Huang, and B. M. Kurkoski, "Sufficient statistic memory approximate message passing," Proc. 2022 IEEE Int. Symp. Inf. Theory, Espoo, Finland, July 2022.[Matlab][Slides]
- L. Liu, S. Liang, and L. Ping, "Capacity optimality of OAMP in coded large unitarily invariant systems," Proc. 2022 IEEE Int. Symp. Inf. Theory, Espoo, Finland, July 2022. [Matlab]][Slides]
- Y. Chi, L. Liu*, G. Song, C. Yuen, Y. L. Guan, and Y. Li, "Capacity optimal coded generalized MU-MIMO," Proc. 2022 IEEE Int. Symp. Inf. Theory, Espoo, Finland, July 2022. [Slides]
□ L. Liu, S. Huang, and B. M. Kurkoski, "Sufficient statistic memory AMP," arXiv preprint: arXiv:2112.15327, Jan. 2022. (submitted to IEEE Transactions on Information Theory) [Matlab][Slides]
A distinguished feature of the AMP-type algorithms is that their dynamics can be rigorously described by state evolution. However, state evolution does not necessarily guarantee the convergence of iterative algorithms. To solve the convergence problem of AMP-type algorithms in principle, this paper proposes a memory AMP (MAMP) under a sufficient statistic condition, named sufficient statistic MAMP (SS-MAMP).
- We show that the covariance matrices of SS-MAMP are L-banded and convergent. Given an arbitrary MAMP, we can construct an SS-MAMP by damping, which not only ensures the convergence of MAMP, but also preserves the orthogonality of MAMP, i.e., its dynamics can be rigorously described by state evolution.
- We prove that the sufficient statistic of Bayes-optimal OAMP/VAMP (BO-OAMP/VAMP) and reveal two interesting properties of BO-OAMP/VAMP: 1) the covariance matrices are L-banded and are convergent, and 2) damping and memory are useless (i.e., do not bring performance improvement).
- We construct a sufficient statistic Bayes-optimal MAMP, which outperforms the original BO-MAMP.
□ L. Liu, S. Liang, and L. Ping, "Capacity optimality of OAMP: Beyond IID sensing matrices and Gaussian signaling," arXiv preprint: arXiv:2108.08503, Aug. 2021. [Matlab][Slides]
In this work, we focus on the fundamental open problem: How to achieve the information-theoretic limit (i.e. constrained capacity) of a large linear system with a non-IID sensing (i.e., right-unitarily-invariant) matrix and non-Gaussian signaling? As a result, a capacity-achieving coded OAMP is designed based on matched FEC coding.
Note: This work is an extension of our previous work "Capacity optimality of AMP in coded systems", which shows the capacity optimality of a coded AMP for IID sensing matrix. For non-IID sensing matrices, AMP does not work well. This work is also an extension of our previous work "Capacity-achieving MIMO-NOMA: Iterative LMMSE detection", which shows the Gaussian capacity-achieving of Turbo LMMSE with Gaussian signaling. However, for practical non-Gaussian signaling, Turbo is not capacity optimal anymore!
□ L. Liu, C. Liang, J. Ma, and L. Ping, "Capacity optimality of AMP in coded systems," IEEE Transactions on Information Theory, vol. 67, no. 7, 4929-4445, July 2021, arXiv preprint arXiv:1901.09559, 2019. [Matlab][Slides][Video]
In this work, we focus on the following fundamental open problem in random linear systems: How to design a low-complexity strategy to achieve the information-theoretic limit of a random linear system with non-Gaussian input distributions? As a result, a low-complexity capacity-achieving coded AMP is designed based on matched FEC coding. In addition, we show that the conventional Turbo method is sub-optimal for non-Gaussian signaling. Apart from that, particular irregular LDPC codes are designed for AMP to obtain capacity-approaching BER performances for various system loads and SNRs.
Note: This is an extension of our previous work "Capacity-achieving MIMO-NOMA: Iterative LMMSE detection", which shows the Gaussian capacity-achieving of Turbo LMMSE with Gaussian signaling. However, for non-Gaussian signaling, Turbo is not capacity optimal anymore!
Journal
Journal
Year-2023:
□ S. Huang, L. Liu and B. M. Kurkoski, "Algebra of L-banded matrices," in IEEE Access, vol. 11, pp. 17658-17664, 2023.
□ M. Yue, L. Liu, and X. Yuan, "RIS-Aided Multiuser MIMO-OFDM with Linear Precoding and Iterative Detection: Analysis and Optimization," IEEE Transactions on Wireless Communications, Mar. 2023. (Accepted)
Year-2022:
□ L. Liu, S. Huang, and B. M. Kurkoski, "Memory AMP," IEEE Transactions on Information Theory, vol. 68, no. 12, pp. 8015-8039, Dec. 2022. [Matlab][Slides][Video]
□ L. Liu, S. Huang, and B. M. Kurkoski, "Sufficient statistic memory AMP," arXiv preprint: arXiv:2112.15327, Jan. 2022. (submitted to IEEE Transactions on Information Theory)
□ L. Liu, Y. Cheng, S. Liang, J. H. Manton, and L. Ping, "On orthogonal approximate message passing," arXiv preprint: arXiv:2203.00224, March 2022.
□ F. Tian, L. Liu and X. Chen, "Generalized Memory Approximate Message Passing for Generalized Linear Model," in IEEE Transactions on Signal Processing, vol. 70, pp. 6404-6418, 2022. [Matlab]
□ Y. Chi, L. Liu*, G. Song, Y. Li, Y. L. Guan, and C. Yuen, ``Constrained capacity Optimal generalized multi-user MIMO: A theoretical and practical framework," IEEE Transactions on Communications, vol. 70, no. 12, pp. 8086-8104, Dec. 2022. [Slides]
□ F. Tian, X. Chen, L. Liu, D. W. K. Ng, "Massive unsourced random access over Rician fading channels: Design, analysis, and optimization," IEEE Internet of Things Journal, vol. 9, no. 18, pp. 17675-17688, 15 Sept. 2022.
Year-2021:
□ L. Liu, C. Liang, J. Ma, and L. Ping, "Capacity optimality of AMP in coded systems," IEEE Transactions on Information Theory, vol. 67, no. 7, 4929-4445, July 2021, arXiv preprint arXiv:1901.09559, 2019. [Matlab][Slides][Video]
□ L. Liu, S. Liang, and L. Ping, "Capacity optimality of OAMP: Beyond IID sensing matrices and Gaussian signaling," arXiv preprint: arXiv:2108.08503, Aug. 2021. [Matlab] □ Y. Cheng, L. Liu, L. Ping, "Orthogonal AMP for massive access in channels with spatial and temporal correlations," in IEEE Journal on Selected Areas in Communications, vol. 39, no. 3, 726-740, March 2021.
□ M. Yue, L. Liu, and X. Yuan, "Practical RIS-Aided Coded Systems: Joint Precoding and Passive Beamforming," IEEE Wireless Communications Letters, vol. 10, no. 11, 2345-2349, 2021.
Year-2020:
□ Y. Cheng, L. Liu, L. Ping, "An integral-based approach to orthogonal AMP," in IEEE Signal Processing Letters, vol. 28, 194-198, Dec. 2020.
□ Z. Zhang, Y. Li, C. Huang, Q. Guo, L. Liu, C. Yuen, and Y. L. Guan, "User activity detection and channel estimation for grant-gree random access in LEO satellite-enabled internet-of-things," IEEE Internet of Things Journal, vol. 7, no. 9, 8811-8825, Mar. 2020.
Year-2019:
□ L. Liu, Y. Chi, C. Yuen, Y. L. Guan, and Y. Li, "Capacity-achieving MIMO-NOMA: Iterative LMMSE detection," IEEE Transactions on Signal Processing, vol. 67, no. 7, 1758 - 1773, April 2019. [C++] [Slides] [Highly-Cited Paper]
□ L. Liu, C. Yuen, Y. L. Guan, Y. Li, and C. Huang, "Gaussian message passing for overloaded massive MIMO-NOMA," IEEE Transactions on Wireless Communications, vol. 18, no. 1, 210 - 226, Jan. 2019. [Matlab] [Slides] [Highly-Cited Paper]
□ L. Liu, Y. Li, C. Huang, C. Yuen, and G. Y. Liang, "A new insight into GAMP and AMP," IEEE Transactions on Vehicular Technology, vol. 68, no. 8, pp. 8264-8269, Aug. 2019. [Matlab]
□ J. Ma, L. Liu*, X. Yuan, and L. Ping, "On orthogonal AMP in coded linear vector systems," IEEE Transactions on Wireless Communications, 18(12), 6487-6501, Oct. 2019.
□ C. Huang, L. Liu*, C. Yuen, and S. Sun, "Iterative channel estimation using LSE and sparse message passing for mmWave MIMO systems," IEEE Transactions on Signal Processing, vol. 67, no. 1, pp. 245 - 259, Jan. 2019. [Highly-Cited Paper]
□ Y. Hu, C. Liang, L. Liu*, C. Y, Y. Y, and L. Ping "Interleave-division multiple access in high rate applications," IEEE Communications Letter, vol. 8, no. 2, pp 476-479, April 2019.
□ Y. Chi, L. Liu, J. Guo, G. Song, C. Yuen, and Y. L. Guan, "Variable-rate coding with constant BER for NOMA via multilevel IRA coding," IEEE Transactions on Vehicular Technology, vol. 68, no. 5, 5149-5153, May 2019.
□ Z. Zhang, Y. Li, L. Liu, and W. Hou, "Fixed-symbol aided random access scheme for machine-to-machine communications," IEEE Access, vol. 7, 52913 - 52928, April, 2019.
Year-2018:
□ Y. Chi, L. Liu, G. Song, C. Yuen, Y. L. Guan, and Y. Li, "Practical MIMO-NOMA: Low complexity and capacity-approaching solution," IEEE Transactions on Wireless Communications, vol. 17, no. 9, 6251-6264, Sept. 2018. [C++]
□ C. Huang, L. Liu, and C. Yuen, "Asymptotically optimal estimation algorithm for the sparse signal with arbitrary distributions," IEEE Transactions on Vehicular Technology, vol. 67, no. 10, 10070-10075, July 2018.
□ Y. Su, Y. Li, X. Wu, and L. Liu, "Outage performance for amplify-and-forward two-hop multiple-access channel," IET Communications, vol. 12, no. 2, 205-213, Feb. 2018.
Year-2017:
□ L. Liu, Y. Liang, and Y. Li, "A new upper bound on the achievable rate of relay channel with MIP-QF strategy," IEEE Transactions on Vehicular Technology, vol. 66, no. 8, 6787-6800, Aug. 2017.
□ L. Liu, Y. Li , C. Yuen, Y. L. Guan, and Y. Sun, "Joint source-channel coding for asymmetric Slepian-Wolf multiple access relay channel," IEEE Wireless Communications Letters, vol. 6, no. 5, 642-645, Oct 2017.
Year-2016:
□ L. Liu, C. Yuen, Y. L. Guan, Y. Li, and Y. Su, "Convergence analysis and assurance for Gaussian message passing iterative detector in massive MU-MIMO systems," IEEE Transactions on Wireless Communications, vol. 15, no. 9, 6487-6501, Sept. 2016. [matlab] [Slides]
□ L. Liu, Y. Li, Y. Su, and Y. Sun, "Quantize-and-forward strategy for interleave division multiple-access relay channel," IEEE Transactions on Vehicular Technology, vol. 65, no. 3, 1808-1814, Mar. 2016.
Year-2015 :
□ Y Su, Y Li, G Song, and L Liu, "Achievable rate regions of multi-way relay channel with direct links," IET Communications, 9 (7), 947-959, May 2015.
□ 苏玉萍， 李颖， 刘雷, "干扰受限的两跳多接入信道的中断概率分析," 电子学报, 43 (12), 2414-2420, Mar 2015.
Conference
Conference
□ L. Liu, S. Huang, and B. M. Kurkoski, "Sufficient statistic memory approximate message passing," Proc. 2022 IEEE Int. Symp. Inf. Theory, Espoo, Finland, July 2022. [Matlab][Slides]
□ L. Liu, S. Liang, and L. Ping, "Capacity optimality of OAMP in coded large unitarily invariant systems," Proc. 2022 IEEE Int. Symp. Inf. Theory, Espoo, Finland, July 2022. [Matlab]][Slides]
□ Y. Chi, L. Liu*, G. Song, Y. Li, Y. L. Guan, and C. Yuen, "Capacity optimal coded generalized MU-MIMO," Proc. 2022 IEEE Int. Symp. Inf. Theory, Espoo, Finland, July 2022. [Slides]
□ L. Liu, S. Huang, and B. M. Kurkoski, "Memory approximate message passing," Proc. 2021 IEEE Int. Symp. Inf. Theory, pp. 1379-1384, Melbourne, Australia, July 2021. [Matlab][Slides][Video]
□ L. Liu, C. Liang, J. Ma, and L. Ping, "Capacity optimality of AMP in coded systems," Proc. 2021 IEEE Int. Symp. Inf. Theory, pp. 1588-1593, Melbourne, Australia, July 2021. [Matlab][Slides][Video]
□ W. Li, L. Liu*, and B. M. Kurkoski, "Irregularly Clipped Sparse Regression Codes," IEEE ITW 2021, Oct. 2021.[Slides][Video]
□ F. Tian, X. Chen, L. Liu, D. W. K. Ng, "Design of massive unsourced random access over Rician channels," 2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Sept. 2021.
□ J. Ma, L. Liu*, Y. Xiao, and L. Ping, "Iterative detection in coded linear systems based on orthogonal AMP," IEEE ISTC, Hong Kong, Dec 2018. [Slides]
□ Y. Hu, C. Liang, L. Liu, C. Yan, Y. Yuan, and L. Ping, "Interleave division multiple access for high overloading applications," IEEE ISTC, Hong Kong, Dec 2018.
□ Z. Zhang, Y. Li, L. Liu, and H. Han, "Sparse message passing based preamble estimation for crowded M2M communications," IEEE ICC, USA, May 2018.
□ L. Liu, C. Huang, Y. Chi, C. Yuen, Y. L. Guan, and Y. Li, "Sparse vector recovery: Bernoulli-Gaussian message passing," IEEE Globecom, Singapore, Dec 2017. [Matlab][Slides]
□ Y. Chi, L. Liu, G. Song, C. Yuen, Y. L. Guan, and Y. Li, "Message passing in C-RAN: Joint user activity and signal detection," IEEE Globecom, Singapore, Dec 2017.
□ T. S. Abeywickrama, L. Liu, Y. Chi, and C. Yuen, "Over-the-air implementation of uplink NOMA," IEEE Globecom, Singapore, Dec 2017.
□ L. Liu, C. Yuen, Y. L. Guan, Y. Li, and C. Huang, "Gaussian message passing iterative detection for MIMO-NOMA systems with massive access," IEEE Globecom, Washington, DC, USA, Dec 2016. [Matlab] [Slides]
□ C. Huang, L. Liu, C. Yuen, and S. Sun, "A LSE and Sparse message passing-based channel estimation for mmWave MIMO systems," IEEE Globecom Workshops, Washington, DC, USA, Dec 2016.
□ L. Liu, C. Yuen, Y. L. Guan, and Y. Li, "Capacity-achieving iterative LMMSE detection for MIMO-NOMA systems," IEEE ICC, Kuala Lumpur, Malaysia, May 2016.[C++] [Slides]
□ L. Liu, C. Yuen, Y. L. Guan, Y. Li, and Y. Su, "A low-complexity Gaussian message passing iterative detector for massive MU-MIMO systems," IEEE ICICS, Singapore, Dec. 2015. [Matlab] [Slides]
Important Notes:
□ Wencong Li and Lei Liu, "LMMSE Estimation", JAIST, Nov. 2020.
□ Feiyan Tian and Lei Liu, "LMMSE (FFT version)", ZJU & JAIST, Jan. 2021.
□ Wencong Li and, Lei Liu, "Bernoulli-Gaussian Signal Estimation", JAIST, Dec. 2020.
□ Feiyan Tian and Lei Liu, "Orthogonalization", ZJU & JAIST, Dec. 2020.
□ Feiyan Tian and Lei Liu, "Declipping via Erfc", ZJU & JAIST, Mar. 2021.
□ Xuehui Chen, Yuhao Chi and Lei Liu, "GAMP and State Evolution", XDU & ZJU, Mar. 2023.
□ Xuehui Chen, Yuhao Chi and Lei Liu, "GOAMP with Unitary Matrices", XDU & ZJU, Mar. 2023.
□ Shunqi Huang, Yuzhi Yang and Lei Liu, "LDPC Decoding", JAIST & ZJU, April 2023.
PhD Thesis
PhD Thesis
□ Lei Liu, “非正交多址接入系统的检测及量化算法研究,” Xidian University, Xi'an, Nov. 2016. (In Chinese)
Useful Documents:
Useful Documents:
□ Latex Mathematical Symbols, Comprehensive Latex Symbol List