no code implementations • 25 Jul 2024 • Jun Lu, Lei Liu, Shunqi Huang, Ning Wei, Xiaoming Chen
Approximate message passing (AMP) algorithms are iterative methods for signal recovery in noisy linear systems.
no code implementations • 15 Mar 2023 • Yao Ge, Lei Liu, Shunqi Huang, David González G., Yong Liang Guan, Zhi Ding
Efficient signal detectors are rather important yet challenging to achieve satisfactory performance for large-scale communication systems.
no code implementations • 20 Dec 2022 • Shunqi Huang, Lei Liu, Brian M. Kurkoski
Damping is commonly employed to ensure the convergence of iterative algorithms.
no code implementations • 23 Jun 2022 • Lei Liu, Shunqi Huang, Brian M. Kurkoski
Approximate message passing (AMP) type algorithms have been widely used in the signal reconstruction of certain large random linear systems.
no code implementations • 31 Dec 2021 • Lei Liu, Shunqi Huang, Yuzhi Yang, Zhaoyang Zhang, Brian M. Kurkoski
Given an arbitrary MAMP, we can construct an SS-MAMP by damping, which not only ensures the convergence of the state evolution, but also preserves the orthogonality, i. e., its dynamics can be correctly described by state evolution.
no code implementations • 4 Jun 2021 • Lei Liu, Shunqi Huang, Brian M. Kurkoski
Approximate message passing (AMP) is a low-cost iterative parameter-estimation technique for certain high-dimensional linear systems with non-Gaussian distributions.
2 code implementations • 20 Dec 2020 • Lei Liu, Shunqi Huang, Brian M. Kurkoski
To asymptotically characterize the performance of BO-MAMP, a state evolution is derived.