Bayesian channel estimation algorithms for massive MIMO systems with hybrid analog-digital processing and low-resolution ADCs
We address the problem of channel estimation in massive multiple-input multiple-output
(Massive MIMO) systems where both hybrid analog-digital processing and low-resolution …
(Massive MIMO) systems where both hybrid analog-digital processing and low-resolution …
Finite-alphabet precoding for massive MU-MIMO with low-resolution DACs
Massive multiuser multiple-input multiple-output (MU-MIMO) systems are expected to be the
core technology in fifth-generation wireless systems because they significantly improve …
core technology in fifth-generation wireless systems because they significantly improve …
A unified Bayesian inference framework for generalized linear models
In this letter, we present a unified Bayesian inference framework for generalized linear
models (GLM), which iteratively reduces the GLM problem to a sequence of standard linear …
models (GLM), which iteratively reduces the GLM problem to a sequence of standard linear …
Generalized approximate message passing for unlimited sampling of sparse signals
In this paper we consider the generalized approximate message passing (GAMP) algorithm
for recovering a sparse signal from modulo samples of randomized projections of the …
for recovering a sparse signal from modulo samples of randomized projections of the …
Distributed distortion-rate optimized compressed sensing in wireless sensor networks
M Leinonen, M Codreanu… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
This paper addresses lossy distributed source coding for acquiring correlated sparse
sources via compressed sensing (CS) in wireless sensor networks. Noisy CS measurements …
sources via compressed sensing (CS) in wireless sensor networks. Noisy CS measurements …
Efficient channel estimation in millimeter wave hybrid MIMO systems with low resolution ADCs
This paper proposes an efficient channel estimation algorithm for millimeter wave
(mmWave) systems with a hybrid analog-digital multiple-input multiple-output (MIMO) …
(mmWave) systems with a hybrid analog-digital multiple-input multiple-output (MIMO) …
[HTML][HTML] Quantization of compressive samples with stable and robust recovery
In this paper we study the quantization stage that is implicit in any compressed sensing
signal acquisition paradigm. We propose using Sigma–Delta (ΣΔ) quantization and a …
signal acquisition paradigm. We propose using Sigma–Delta (ΣΔ) quantization and a …
Optimal data detection in large MIMO
Large multiple-input multiple-output (MIMO) appears in massive multi-user MIMO and
randomly-spread code-division multiple access (CDMA)-based wireless systems. In order to …
randomly-spread code-division multiple access (CDMA)-based wireless systems. In order to …
Rate-distortion performance of lossy compressed sensing of sparse sources
We investigate lossy compressed sensing (CS) of a hidden, or remote, source, where a
sensor observes a sparse information source indirectly. The compressed noisy …
sensor observes a sparse information source indirectly. The compressed noisy …
Adaptive one‐bit quantisation via approximate message passing with nearest neighbour sparsity pattern learning
In this study, the problem of recovering structured sparse signals with a priori distribution
whose structure patterns are unknown is studied from one‐bit adaptive (AD) quantised …
whose structure patterns are unknown is studied from one‐bit adaptive (AD) quantised …