activity
20192024
most citedTwo-Timescale Design for RIS-aided Cell-free Massive MIMO Systems with Imperfect CSI

5 citations · 12 across the 9 of their papers we have counts for

collaborators

9 papers

eess.SP2024★ 2 cited

Spectral Efficiency Maximization for Active RIS-aided Cell-Free Massive MIMO Systems with Imperfect CSI

Mahdi Eskandari, Huiling Zhu, Jiangzhou Wang

A cell-free network merged with active reconfigurable reflecting surfaces (RIS) is investigated in this paper. Based on the imperfect channel state information (CSI), the aggregate…

eess.SP2023★ 2 cited

Multi-fidelity Bayesian Optimisation of Syngas Fermentation Simulators

Mahdi Eskandari, Lars Puiman, Jakob Zeitler

A Bayesian optimization approach for maximizing the gas conversion rate in an industrial-scale bioreactor for syngas fermentation is presented. We have access to a high-fidelity, c…

eess.SP2023★ 5 cited

Two-Timescale Design for RIS-aided Cell-free Massive MIMO Systems with Imperfect CSI

Mahdi Eskandari, Kangda Zhi, Huiling Zhu +2

The objective of this paper is to evaluate the effectiveness of a two-timescale transmission design in cell-free massive multi-input multiple-output (MIMO) systems incorporating re…

eess.SP2022★ 2 cited

Statistical CSI-based Beamforming for RIS-Aided Multiuser MISO Systems using Deep Reinforcement Learning

Mahdi Eskandari, Huiling Zhu, Arman Shojaeifard +1

The paper presents a joint beamforming algorithm using statistical channel state information (S-CSI) for reconfigurable intelligent surfaces (RIS) for multiuser MISO wireless commu…

eess.SP2022★ 1 cited

Smart Interference Management xApp using Deep Reinforcement Learning

Mahdi Eskandari, Shipra Kapoor, Keith Briggs +3

Interference continues to be a key limiting factor in cellular radio access network (RAN) deployments. Effective, data-driven, self-adapting radio resource management (RRM) solutio…

eess.SP2020

A Gridless Compressive Sensing Based Channel Estimation for Millimeter Wave Massive MIMO Systems from 1-Bit Measurements

Mahdi Eskandari, Hamidreza Bakhshi

This paper considers the problem of estimating the sparse millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) OFDM channel from 1-bit quantized measurements. Unl…

eess.SP2019

A Gridless Compressive Sensing Based Channel Estimation for Millimeter Wave MIMO OFDM Systems with One-Bit Quantization

Mahdi Eskandari, Hamidreza Bakhshi

This paper considers the problem of estimating the sparse mmWave massive multiple input - multiple output (MIMO) OFDM channel from one-bit quantized measurements. Unlike previous g…

eess.SP2019

A Frequency Domain Channel Estimation Based on Atomic Norm Minimization for Frequency Selective MmWave MIMO Systems

Mahdi Eskandari, Hamidreza Bakhshi

In this study, a channel estimator for millimeter wave (mmWave) systems is proposed. By considering the sparse nature of channels in millimeter wave band, the channel estimation pr…

eess.SP2019

Channel Estimation for MIMO Hybrid Architectures with Low Resolution ADCs for mmWave Communication

Mahdi Eskandari, Hamidreza Bakhshi

Hybrid analog/digital architectures and receivers with low-resolution analog-to-digital converters (ADCs) are two low power solutions for wireless systems with large antenna arrays…