activity
20052024
most citedMassive MIMO for Next Generation Wireless Systems

7k citations · 13.5k across the 34 of their papers we have counts for

collaborators

40 papers

eess.SP2024

How Much Power Must We Extract From a Receiver Antenna to Effect Communications?

Thomas L. Marzetta, Brian McMinn, Amritpal Singh +1

Subject to the laws of classical physics - the science that governs the design of today's wireless communication systems - there is no need to extract power from a receiver antenna…

cs.IT2024★ 37 cited

Towards 6G MIMO: Massive Spatial Multiplexing, Dense Arrays, and Interplay Between Electromagnetics and Processing

Emil Björnson, Chan-Byoung Chae, Robert W. Heath +7

The increasing demand for wireless data transfer has been the driving force behind the widespread adoption of Massive MIMO (multiple-input multiple-output) technology in 5G. The ne…

cs.IT2023

Shannon Theory for Wireless Communication in a Resonant Chamber

Amritpal Singh, Thomas Marzetta

A closed electromagnetic resonant chamber (RC) is a highly favorable artificial environment for wireless communication. A pair of antennas within the chamber constitutes a two-port…

cs.IT2023

Wide-Aperture MIMO via Reflection off a Smooth Surface

Andrea Pizzo, Angel Lozano, Sundeep Rangan +1

This paper provides a deterministic channel model for a scenario where wireless connectivity is established through a reflection off a smooth planar surface of an infinite extent.…

cs.IT2022

Line-of-Sight MIMO via Reflection From a Smooth Surface

Andrea Pizzo, Angel Lozano, Sundeep Rangan +1

We provide a deterministic channel model for a scenario where wireless connectivity is established through a reflection from a planar smooth surface of an infinite extent. The deve…

cs.IT2022

Coupling Matrix-based Beamforming for Superdirective Antenna Arrays

Liangcheng Han, Haifan Yin, Thomas L. Marzetta

In most multiple-input multiple-output (MIMO) communication systems, e.g., Massive MIMO, the antenna spacing is generally no less than half a wavelength. It helps to reduce the mut…

cs.IT2021★ 1 cited

MRT-based Joint Unicast and Multigroup Multicast Transmission in Massive MIMO Systems

Meysam Sadeghi, Emil Björnson, Erik G. Larsson +2

We study joint unicast and multigroup multicast transmission in single-cell massive multiple-input-multiple-output (MIMO) systems, under maximum ratio transmission. For the unicast…

eess.SP2021★ 92 cited

Nyquist-Sampling and Degrees of Freedom of Electromagnetic Fields

Andrea Pizzo, Andrea de Jesus Torres, Luca Sanguinetti +1

A signal space approach is presented to study the Nyquist sampling, number of degrees of freedom and reconstruction of an electromagnetic field under arbitrary scattering condition…

cs.IT2021

How Does Cell-Free Massive MIMO Support Multiple Federated Learning Groups?

Tung T. Vu, Hien Quoc Ngo, Thomas L. Marzetta +1

Federated learning (FL) has been considered as a promising learning framework for future machine learning systems due to its privacy preservation and communication efficiency. In b…

cs.IT2021★ 1 cited

Fourier Plane-Wave Series Expansion for Holographic MIMO Communications

Andrea Pizzo, Luca Sanguinetti, Thomas L. Marzetta

Imagine a MIMO communication system that fully exploits the propagation characteristics offered by an electromagnetic channel and ultimately approaches the limits imposed by wirele…

cs.IT2021

Multi-point Coordination in Massive MIMO Systems with Sectorized Antennas

Shahram Shahsavari, Mehrdad Nosrati, Parisa Hassanzadeh +3

Non-cooperative cellular massive MIMO, combined with power control, is known to lead to significant improvements in per-user throughput compared with conventional LTE technology. I…

cs.IT2021

Spatial Characterization of Electromagnetic Random Channels

Andrea Pizzo, Luca Sanguinetti, Thomas L. Marzetta

The majority of stochastic channel models rely on the electromagnetic far-field assumption, which allows to decompose the channel in terms of plane waves. The far-field assumption…

cs.IT2020

Holographic MIMO Communications Under Spatially-Stationary Scattering

Andrea Pizzo, Thomas Marzetta, Luca Sanguinetti

Holographic MIMO is a spatially-constrained MIMO system with a massive number of antennas, possibly thought of, in its ultimate form, as a spatially-continuous electromagnetic aper…

cs.IT2020

Multiuser MIMO with Large Intelligent Surfaces: Communication Model and Transmit Design

Robin Jess Williams, Pablo Ramírez-Espinosa, Elisabeth de Carvalho +1

This paper proposes a communication model for multiuser multiple-input multiple-output (MIMO) systems based on large intelligent surfaces (LIS), where the LIS is modeled as a colle…

cs.IT2019

A Communication Model for Large Intelligent Surfaces

Robin Jess Williams, Elisabeth De Carvalho, Thomas L. Marzetta

The purpose of this paper is to introduce a communication model for Large Intelligent Surfaces (LIS). A LIS is modelled as a collection of tiny closely spaced antenna elements. Due…

cs.IT2019★ 48 cited

Joint Unicast and Multi-group Multicast Transmission in Massive MIMO Systems

Meysam Sadeghi, Emil Björnson, Erik G. Larsson +2

We study the joint unicast and multi-group multicast transmission in massive multiple-input-multiple-output (MIMO) systems. We consider a system model that accounts for channel est…

cs.IT2019

Degrees of Freedom of Holographic MIMO Channels

Andrea Pizzo, Thomas L. Marzetta, Luca Sanguinetti

We consider spatially-constrained apertures of rectangular symmetry and aim to retrieve the limit to the average number of spatial degrees of freedom (DoF), obtained elsewhere thro…

cs.IT2019

Spatially-Stationary Model for Holographic MIMO Small-Scale Fading

Andrea Pizzo, Thomas L. Marzetta, Luca Sanguinetti

Imagine an array with a massive (possibly uncountably infinite) number of antennas in a compact space. We refer to a system of this sort as Holographic MIMO. Given the impressive p…

eess.SP2019★ 96 cited

Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays

Emil Björnson, Luca Sanguinetti, Henk Wymeersch +2

Massive MIMO (multiple-input multiple-output) is no longer a "wild" or "promising" concept for future cellular networks - in 2018 it became a reality. Base stations (BSs) with 64 f…

cs.IT2017

Multigroup Multicast Precoding in Massive MIMO

Meysam Sadeghi, Emil Björnson, Erik G. Larsson +2

Optimal physical layer multicasting (PLM) is an NP-hard problem that for simplicity has been studied under idealistic assumptions, e.g., availability of perfect channel state infor…

cs.IT2017

Max-Min Fair Transmit Precoding for Multi-group Multicasting in Massive MIMO

Meysam Sadeghi, Emil Björnson, Erik G. Larsson +2

This paper considers the downlink precoding for physical layer multicasting in massive multiple-input-multiple-output (MIMO) systems. We study the max-min fairness (MMF) problem, w…

cs.IT2017★ 3 cited

Performance of Cell-Free Massive MIMO Systems with MMSE and LSFD Receivers

Elina Nayebi, Alexei Ashikhmin, Thomas L. Marzetta +1

Cell-Free Massive MIMO comprises a large number of distributed single-antenna access points (APs) serving a much smaller number of users. There is no partitioning into cells and ea…

cs.IT2017★ 4 cited

Antenna Count for Massive MIMO: 1.9 GHz versus 60 GHz

Erik G. Larsson, Thomas L. Marzetta, Hien Quoc Ngo +1

If we assume line-of-sight propagation and perfect channel state information at the base station -- consistent with slow moving terminals -- then a direct performance comparison be…

cs.IT2017

Uplink Interference Reduction in Large Scale Antenna Systems

Ansuman Adhikary, Alexei Ashikhmin, Thomas L. Marzetta

A massive MIMO system entails a large number (tens or hundreds) of base station antennas serving a much smaller number of terminals. These systems demonstrate large gains in spectr…