activity
20072025
most citedThroughput Analysis of Massive MIMO Uplink with Low-Resolution ADCs

425 citations · 1.4k across the 81 of their papers we have counts for

collaborators

109 papers

eess.SP2025

Insights on the Uplink Operation of a 1-bit Radio-Over-Fiber Architecture in Multi-User D-MIMO Communication

Lise Aabel, Giuseppe Durisi, Frida Olofsson +3

We consider a distributed multiple-input multiple-output (D-MIMO) testbed in which, to enable coherent-phase transmission without over-the-air synchronization, the remote radio hea…

eess.SP2024

Deep-Learning-Based Channel Estimation for Distributed MIMO with 1-bit Radio-Over-Fiber Fronthaul

Alireza Bordbar, Lise Aabel, Christian Häger +2

We consider the problem of pilot-aided, uplink channel estimation in a distributed massive multiple-input multiple-output (MIMO) architecture, in which the access points are connec…

cs.IT2024

EVM Analysis of Distributed Massive MIMO with 1-Bit Radio-Over-Fiber Fronthaul

Anzhong Hu, Lise Aabel, Giuseppe Durisi +4

We analyze the uplink performance of a distributed massive multiple-input multiple-output (MIMO) architecture in which the remotely located access points (APs) are connected to a c…

cs.IT2024★ 1 cited

Integrated Communication, Localization, and Sensing in 6G D-MIMO Networks

Hao Guo, Henk Wymeersch, Behrooz Makki +10

Future generations of mobile networks call for concurrent sensing and communication functionalities in the same hardware and/or spectrum. Compared to communication, sensing service…

eess.SP2024

A TDD Distributed MIMO Testbed Using a 1-Bit Radio-Over-Fiber Fronthaul Architecture

Lise Aabel, Sven Jacobsson, Mikael Coldrey +3

We present the uplink and downlink of a time-division duplex distributed multiple-input multiple-output (D-MIMO) testbed, based on a 1-bit radio-over-fiber architecture, which is l…

cs.LG2023★ 6 cited

Generalization Bounds: Perspectives from Information Theory and PAC-Bayes

Fredrik Hellström, Giuseppe Durisi, Benjamin Guedj +1

A fundamental question in theoretical machine learning is generalization. Over the past decades, the PAC-Bayesian approach has been established as a flexible framework to address t…