most citedA Fair Comparison Between Spatial Modulation and Antenna Selection in Massive MIMO Systems

6 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IT2019

An Adaptive Bayesian Framework for Recovery of Sources with Structured Sparsity

Ali Bereyhi, Ralf R. Müller

In oversampled adaptive sensing (OAS), noisy measurements are collected in multiple subframes. The sensing basis in each subframe is adapted according to some posterior information…

cs.IT20191 cited

Robustness of Low-Complexity Massive MIMO Architectures Against Passive Eavesdropping

Ali Bereyhi, Saba Asaad, Ralf R. Müller +3

Invoking large transmit antenna arrays, massive MIMO wiretap settings are capable of suppressing passive eavesdroppers via narrow beamforming towards legitimate terminals. This imp…

cs.IT2019

PAPR-Limited Precoding in Massive MIMO Systems with Reflect- and Transmit-Array Antennas

Ali Bereyhi, Vahid Jamali, Ralf R. Müller +3

Conventional hybrid analog-digital architectures for millimeter-wave massive multiple-input multiple-output (MIMO) systems suffer from poor scalability and high implementational co…

cs.IT2019

Joint User Selection and Precoding in Multiuser MIMO Systems via Group LASSO

Saba Asaad, Ali Bereyhi, Ralf R. Muller +1

Joint user selection and precoding in multiuser MIMO settings can be interpreted as group sparse recovery in linear models. In this problem, a signal with group sparsity is to be r…

cs.IT20196 cited

A Fair Comparison Between Spatial Modulation and Antenna Selection in Massive MIMO Systems

Bernhard Gäde, Ali Bereyhi, Saba Asaad +1

Both antenna selection and spatial modulation allow for low-complexity MIMO transmitters when the number of RF chains is much lower than the number of transmit antennas. In this ma…