Search Results for author: Italo Atzeni

Found 9 papers, 0 papers with code

Metasurface-Based Receivers with $1$-bit ADCs for Multi-User Uplink Communications

no code implementations15 Jan 2024 Panagiotis Gavriilidis, Italo Atzeni, George C. Alexandropoulos

The massive Multiple-Input Multiple-Output (mMIMO) concept has been recently moving forward to extreme scales to address the envisioned requirements of next generation networks.

Doubly 1-Bit Quantized Massive MIMO

no code implementations4 Dec 2023 Italo Atzeni, Antti Tölli, Duy H. N. Nguyen, A. Lee Swindlehurst

Enabling communications in the (sub-)THz band will call for massive multiple-input multiple-output (MIMO) arrays at either the transmit- or receive-side, or at both.

Pilot-Based Uplink Power Control in Single-UE Massive MIMO Systems With 1-Bit ADCs

no code implementations25 Oct 2023 Amila Ravinath, Bikshapathi Gouda, Italo Atzeni, Antti Tölli

We propose uplink power control (PC) methods for massive multiple-input multiple-output systems with 1-bit analog-to-digital converters, which are specifically tailored to address the non-monotonic data detection performance with respect to the transmit power of the user equipment (UE).

Analysis of Oversampling in Uplink Massive MIMO-OFDM with Low-Resolution ADCs

no code implementations30 Jun 2023 Mengyuan Ma, Nhan Thanh Nguyen, Italo Atzeni, Markku Juntti

In particular, we demonstrate that oversampling can effectively improve the sum rate by mitigating the impact of the quantization distortion, especially at high SNR and with very low ADC resolution.

Quantization

Multi-User Data Detection in Massive MIMO with 1-Bit ADCs

no code implementations31 Mar 2023 Amin Radbord, Italo Atzeni, Antti Tölli

We provide new analytical results on the uplink data detection in massive multiple-input multiple-output systems with 1-bit analog-to-digital converters.

A Variational Bayesian Perspective on Massive MIMO Detection

no code implementations23 May 2022 Duy H. N. Nguyen, Italo Atzeni, Antti Tölli, A. Lee Swindlehurst

In this paper, we build upon variational Bayes (VB) inference to design low-complexity multiuser detection algorithms for massive MIMO systems.

Joint Minimum DL-UL Rate Maximization for Cell-Free Massive MIMO

no code implementations12 Oct 2021 Bikshapathi Gouda, Italo Atzeni, Antti Tölli

Numerical results show that, in scenarios with short scheduling blocks, the proposed framework outperforms the case where the DL and UL beamforming strategies are computed individually via two separate bi-directional training phases thanks to the reduced training overhead.

Scheduling

D2D-Aided Multi-Antenna Multicasting under Generalized CSIT

no code implementations2 Feb 2021 Placido Mursia, Italo Atzeni, Mari Kobayashi, David Gesbert

Multicasting, where a base station (BS) wishes to convey the same message to several user equipments (UEs), represents a common yet highly challenging wireless scenario.

Information Theory Information Theory

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