N
Nemanja Stefan Perovic
Researcher at University College Dublin
Publications - 24
Citations - 437
Nemanja Stefan Perovic is an academic researcher from University College Dublin. The author has contributed to research in topics: MIMO & Communication channel. The author has an hindex of 7, co-authored 24 publications receiving 236 citations. Previous affiliations of Nemanja Stefan Perovic include Johannes Kepler University of Linz.
Papers
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Proceedings ArticleDOI
Channel Capacity Optimization Using Reconfigurable Intelligent Surfaces in Indoor mmWave Environments
TL;DR: This work proposes two optimization schemes that exploit the customizing capabilities of the RIS reflection elements in order to maximize the channel capacity and proposes a low-complexity technique called global co-phasing to determine the phase shift values for use at the RIS.
Journal ArticleDOI
Achievable Rate Optimization for MIMO Systems With Reconfigurable Intelligent Surfaces
TL;DR: This work proposes an iterative optimization algorithm that is based on the projected gradient method (PGM) and derives the step size that guarantees the convergence of the proposed algorithm and defines a backtracking line search to improve its convergence rate.
Journal ArticleDOI
Performance of Generalized Spatial Modulation MIMO Over Measured 60GHz Indoor Channels
TL;DR: The capacity and symbol error probability (SEP) of generalized spatial modulation (GSM) multiple-input multiple-output (MIMO) using measured channels that are obtained by channel sounding in an indoor office environment at 60GHz are studied.
Journal ArticleDOI
Receive Spatial Modulation for LOS mmWave Communications Based on TX Beamforming
TL;DR: It is proved that the SEP of RSM in a LOS channel is minimized by imposing orthogonality conditions to the channel matrix, and a simple hardware architecture for the transmitter is proposed, which uses only RF phase shifters for precoding.
Journal ArticleDOI
Optimization of RIS-Aided MIMO Systems Via the Cutoff Rate
TL;DR: This work proposes to use the cutoff rate (CR) as a more tractable metric for optimizing the MI and introduces two optimization methods to maximize the CR, assuming perfect knowledge of the channel state information (CSI).