Massive multiple-input multiple-output (MIMO) is a key technology to meet the user demands
in performance and quality of services (QoS) for next generation communication systems …

Detection techniques for massive multiple-input multiple-output (MIMO) have gained a lot of
attention in both academia and industry. Detection techniques have a significant impact on …

This paper is focused on code-domain non-orthogonal multiple access (CD-NOMA), which
is an emerging paradigm to support massive connectivity for future machine-type wireless …

Signal recovery from unitarily invariant measurements is investigated in this paper. A
message-passing algorithm is formulated on the basis of expectation propagation (EP). A …

Approximate message passing (AMP) is a low-cost iterative parameter-estimation technique
for certain high-dimensional linear systems with non-Gaussian distributions. AMP only …

This paper proposes Bayes-optimal convolutional approximate message-passing (CAMP)
for signal recovery in compressed sensing. CAMP uses the same low-complexity matched …

Orthogonal/vector approximate message-passing (AMP) is a powerful message-passing
(MP) algorithm for signal reconstruction in compressed sensing. This paper proves the …

We consider the problem of signal estimation in a generalized linear model (GLM). GLMs
include many canonical problems in statistical estimation, such as linear regression, phase …

Approximate message passing (AMP) is a low-cost iterative parameter-estimation technique
for certain high-dimensional linear systems with non-Gaussian distributions. However, AMP …

This paper proposes an adaptively scaled belief (ASB) in Gaussian belief propagation
(GaBP) designed for use in large multi-user multi-input multi-output (MU-MIMO) detection …