9 citations · 14 across the 11 of their papers we have counts for
11 papers
Power Allocation for the Base Matrix of Spatially Coupled Sparse Regression Codes
Nian Guo, Shansuo Liang, Wei Han
We investigate power allocation for the base matrix of a spatially coupled sparse regression code (SC-SPARC) for reliable communications over an additive white Gaussian noise chann…
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…
Capacity-Achieving Sparse Regression Codes via Vector Approximate Message Passing
Yizhou Xu, YuHao Liu, ShanSuo Liang +4
Sparse regression codes (SPARCs) are a promising coding scheme that can approach the Shannon limit over Additive White Gaussian Noise (AWGN) channels. Previous works have proven th…
Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise
Teng Fu, YuHao Liu, Jean Barbier +3
We study the performance of a Bayesian statistician who estimates a rank-one signal corrupted by non-symmetric rotationally invariant noise with a generic distribution of singular…
Approximate Message Passing for Multi-Layer Estimation in Rotationally Invariant Models
Yizhou Xu, TianQi Hou, ShanSuo Liang +1
We consider the problem of reconstructing the signal and the hidden variables from observations coming from a multi-layer network with rotationally invariant weight matrices. The m…
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…
An Efficient Two-Stage SPARC Decoder for Massive MIMO Unsourced Random Access
Juntao You, Wenjie Wang, Shansuo Liang +2
In this paper, we study a concatenate coding scheme based on sparse regression code (SPARC) and tree code for unsourced random access in massive multiple-input and multiple-output…
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…
A Tensor-BTD-based Modulation for Massive Unsourced Random Access
Zhenting Luan, Yuchi Wu, Shansuo Liang +3
In this letter, we propose a novel tensor-based modulation scheme for massive unsourced random access. The proposed modulation can be deemed as a summation of third-order tensors,…
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…
Compressed Coding, AMP Based Decoding and Analog Spatial Coupling
Shansuo Liang, Chulong Liang, Junjie Ma +1
This paper considers a compressed-coding scheme that combines compressed sensing with forward error control coding. Approximate message passing (AMP) is used to decode the message.…