18 citations · 42 across the 10 of their papers we have counts for
11 papers
Memory AMP: Overflow Avoidance, Complexity Reduction, and Comparative Analysis
Shunqi Huang, Lei Liu, Brian M. Kurkoski
Approximate message passing (AMP)-type algorithms are widely used for signal recovery in high-dimensional noisy linear systems. Recently, a framework called memory AMP (MAMP) was i…
Orthogonal AMP for Problems with Multiple Measurement Vectors and/or Multiple Transforms
Yiyao Cheng, Lei Liu, Shansuo Liang +2
Approximate message passing (AMP) algorithms break a (high-dimensional) statistical problem into parts then repeatedly solve each part in turn, akin to alternating projections. A d…
RIS-Aided Multiuser MIMO-OFDM with Linear Precoding and Iterative Detection: Analysis and Optimization
Mingyang Yue, Lei Liu, Xiaojun Yuan
In this paper, we consider a reconfigurable intelligence surface (RIS) aided uplink multiuser multi-input multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) syst…
Capacity Optimality of OAMP in Coded Large Unitarily Invariant Systems
Lei Liu, Shansuo Liang, Li Ping
This paper investigates a large unitarily invariant system (LUIS) involving a unitarily invariant sensing matrix, an arbitrary fixed signal distribution, and forward error control…
On Orthogonal Approximate Message Passing
Lei Liu, Yiyao Cheng, Shansuo Liang +2
Approximate Message Passing (AMP) is an efficient iterative parameter-estimation technique for certain high-dimensional linear systems with non-Gaussian distributions, such as spar…
On Capacity Optimality of OAMP: Beyond IID Sensing Matrices and Gaussian Signaling
Lei Liu, Shansuo Liang, Li Ping
This paper investigates a large unitarily invariant system (LUIS) involving a unitarily invariant sensing matrix, an arbitrarily fixed signal distribution, and forward error contro…
Memory Approximate Message Passing
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. However, AMP o…
Irregularly Clipped Sparse Regression Codes
Wencong Li, Lei Liu, Brian M. Kurkoski
Recently, it was found that clipping can significantly improve the section error rate (SER) performance of sparse regression (SR) codes if an optimal clipping threshold is chosen.…
Capacity Optimality of AMP in Coded Systems
Lei Liu, Chulong Liang, Junjie Ma +1
This paper studies a large random matrix system (LRMS) model involving an arbitrary signal distribution and forward error control (FEC) coding. We establish an area property based…
Memory AMP
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. AMP only appli…
Capacity Optimality of AMP in Coded Systems
Lei Liu, Chulong Liang, Junjie Ma +1
This paper studies a large random matrix system (LRMS) model involving an arbitrary signal distribution and forward error control (FEC) coding. We establish an area property based…