17 citations · 65 across the 51 of their papers we have counts for
9 papers · 1 filter
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…
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…
Secure Regularized Zero Forcing for Multiuser MIMOME Channels
Saba Asaad, Ali Bereyhi, Ralf R. Müller +1
This paper proposes a new linear precoding scheme for downlink transmission in MIMOME channels, referred to as secure regularized zero forcing. The scheme modifies regularized zero…
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…
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…
Approximate Message Passing for Indoor THz Channel Estimation
Viktoria Schram, Ali Bereyhi, Jan-Nico Zaech +2
Compressed sensing (CS) deals with the problem of reconstructing a sparse vector from an under-determined set of observations. Approximate message passing (AMP) is a technique used…
RLS Precoding for Massive MIMO Systems with Nonlinear Front-End
Ali Bereyhi, Saba Asaad, Ralf R. Müller +1
To keep massive MIMO systems cost-efficient, power amplifiers with rather small output dynamic ranges are employed. They may distort the transmit signal and degrade the performance…
RLS-Based Detection for Massive Spatial Modulation MIMO
Ali Bereyhi, Saba Asaad, Bernhard Gäde +1
Most detection algorithms in spatial modulation (SM) are formulated as linear regression via the regularized least-squares (RLS) method. In this method, the transmit signal is esti…
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…