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20052021
most citedHardware Impairments Aware Transceiver Design for Full-Duplex Amplify-and-Forward MIMO Relaying

67 citations · 178 across the 38 of their papers we have counts for

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cs.IT2021

Quantization-Aided Secrecy: FD C-RAN Communications with Untrusted Radios

Omid Taghizadeh, Tianyu Yang, Hiroki Iimori +3

In this work, we study a full-duplex (FD) cloud radio access network (C-RAN) from the aspects of infrastructure sharing and information secrecy, where the central unit utilizes FD…

cs.IT2020

Asymptotic Rate Analysis for Impairments-Aware Multi-Carrier FD Massive MIMO Relay Networks utilizing MRT/MRC Strategy

Vimal Radhakrishnan, Omid Taghizadeh, Rudolf Mathar

In this paper, we analyze the asymptotic rate for a multi-carrier (MC) full-duplex (FD) massive multiple input multiple output (mMIMO) decode and forward (DF) relay system which se…

cs.IT2019★ 1 cited

Rate Splitting for Massive MIMO Multi-carrier system using Full Duplex Decode and Forward Relay with Hardware Impairments

Vimal Radhakrishnan, Omid Taghizadeh, Rudolf Mathar

In this paper, we address the power allocation problem for a decode and forward (DF) relay system, where a massive multiple-input-multiple-output (mMIMO) multi-carrier (MC) base st…

cs.IT2019★ 20 cited

Sensing Matrix Design and Sparse Recovery on the Sphere and the Rotation Group

Arya Bangun, Arash Behboodi, Rudolf Mathar

In this paper, {the goal is to design deterministic sampling patterns on the sphere and the rotation group} and, thereby, construct sensing matrices for sparse recovery of band-lim…

cs.IT2019

Localizing an Unknown Number of mmW Transmitters Under Path Loss Model Uncertainties

Ehsan Zandi, Rudolf Mathar

This work estimates the position and the transmit power of multiple co-channel wireless transmitters under model uncertainties. The model uncertainties include the number of the ta…

cs.IT2019★ 1 cited

The Restricted Isometry Property of Block Diagonal Matrices for Group-Sparse Signal Recovery

Niklas Koep, Arash Behboodi, Rudolf Mathar

Group-sparsity is a common low-complexity signal model with widespread application across various domains of science and engineering. The recovery of such signal ensembles from com…