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03/20/2023
Sionna RT: Differentiable Ray Tracing for Radio Propagation Modeling
Sionna is a GPU-accelerated open-source library for link-level simulatio...
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12/15/2022
DUIDD: Deep-Unfolded Interleaved Detection and Decoding for MIMO Wireless Systems
Iterative detection and decoding (IDD) is known to achieve near-capacity...
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11/15/2022
Attacking and Defending Deep-Learning-Based Off-Device Wireless Positioning Systems
Localization services for wireless devices play an increasingly importan...
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07/29/2022
Graph Neural Networks for Channel Decoding
In this work, we propose a fully differentiable graph neural network (GN...
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06/08/2022
Mixed-Timescale Deep-Unfolding for Joint Channel Estimation and Hybrid Beamforming
In massive multiple-input multiple-output (MIMO) systems, hybrid analog-...
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05/22/2022
Deep Learning-Based Synchronization for Uplink NB-IoT
We propose a neural network (NN)-based algorithm for device detection an...
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03/22/2022
Sionna: An Open-Source Library for Next-Generation Physical Layer Research
Sionna is a GPU-accelerated open-source library for link-level simulatio...
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03/11/2022
Bit-Metric Decoding Rate in Multi-User MIMO Systems: Applications
This is the second part of a two-part paper that focuses on link-adaptat...
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03/11/2022
Bit-Metric Decoding Rate in Multi-User MIMO Systems: Theory
Link-adaptation (LA) is one of the most important aspects of wireless co...
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01/14/2022
Waveform Learning for Reduced Out-of-Band Emissions Under a Nonlinear Power Amplifier
Machine learning (ML) has shown great promise in optimizing various aspe...
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10/22/2021
Two-Timescale End-to-End Learning for Channel Acquisition and Hybrid Precoding
In this paper, we propose an end-to-end deep learning-based joint transc...
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10/21/2021
Improving Channel Charting using a Split Triplet Loss and an Inertial Regularizer
Channel charting is an emerging technology that enables self-supervised ...
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10/21/2021
Learning OFDM Waveforms with PAPR and ACLR Constraints
An attractive research direction for future communication systems is the...
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09/02/2021
Waveform Learning for Next-Generation Wireless Communication Systems
We propose a learning-based method for the joint design of a transmit an...
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08/16/2021
The Emergence of Wireless MAC Protocols with Multi-Agent Reinforcement Learning
In this paper, we propose a new framework, exploiting the multi-agent de...
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06/30/2021
Machine Learning-enhanced Receive Processing for MU-MIMO OFDM Systems
Machine learning (ML) can be used in various ways to improve multi-user ...
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06/30/2021
End-to-End Learning of OFDM Waveforms with PAPR and ACLR Constraints
Orthogonal frequency-division multiplexing (OFDM) is widely used in mode...
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06/29/2021
End-to-end Waveform Learning Through Joint Optimization of Pulse and Constellation Shaping
As communication systems are foreseen to enable new services such as joi...
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04/14/2021
Unsupervised Learning in Next-Generation Networks: Real-Time Performance Self-Diagnosis
This letter demonstrates the use of unsupervised machine learning to ena...
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01/20/2021
Trimming the Fat from OFDM: Pilot- and CP-less Communication with End-to-end Learning
Orthogonal frequency division multiplexing (OFDM) is one of the dominant...
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12/15/2020
Bayesian Optimization for Radio Resource Management: Open Loop Power Control
The purpose of this paper is to provide the reader with an accessible ye...
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12/15/2020
Towards a 6G AI-Native Air Interface
Each generation of cellular communication systems is marked by a definin...
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12/15/2020
Machine Learning for MU-MIMO Receive Processing in OFDM Systems
Machine learning (ML) starts to be widely used to enhance the performanc...
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09/11/2020
End-to-end Learning for OFDM: From Neural Receivers to Pilotless Communication
Previous studies have demonstrated that end-to-end learning enables sign...
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07/20/2020
Towards Joint Learning of Optimal Signaling and Wireless Channel Access
Communication protocols are the languages used by network nodes to accom...
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04/10/2020
Joint Learning of Probabilistic and Geometric Shaping for Coded Modulation Systems
We introduce a trainable coded modulation scheme that enables joint opti...
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02/07/2020
Deep HyperNetwork-Based MIMO Detection
Optimal symbol detection for multiple-input multiple-output (MIMO) syste...
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11/29/2019
Trainable Communication Systems: Concepts and Prototype
We consider a trainable point-to-point communication system, where both ...
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09/14/2019
Learning to Communicate and Energize: Modulation, Coding and Multiple Access Designs for Wireless Information-Power Transmission
The explosion of the number of low-power devices in the next decades cal...
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08/30/2019
Learning Modulation Design for SWIPT with Nonlinear Energy Harvester: Large and Small Signal Power Regimes
Nonlinear energy harvesters (EH) behave differently depending on the ran...
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07/02/2019
"Machine LLRning": Learning to Softly Demodulate
Soft demodulation, or demapping, of received symbols back into their con...
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06/18/2019
Joint Learning of Geometric and Probabilistic Constellation Shaping
The choice of constellations largely affects the performance of communic...
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06/11/2019
Adaptive Neural Signal Detection for Massive MIMO
Symbol detection for Massive Multiple-Input Multiple-Output (MIMO) is a ...
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05/20/2019
Transmitter Classification With Supervised Deep Learning
Hardware imperfections in RF transmitters introduce features that can be...
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04/06/2019
Towards Massive MIMO 2.0: Understanding spatial correlation, interference suppression, and pilot contamination
Since the seminal paper by Marzetta from 2010, Massive MIMO has changed ...
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03/21/2019
Smart Radio Environments Empowered by AI Reconfigurable Meta-Surfaces: An Idea Whose Time Has Come
Future wireless networks are expected to constitute a distributed intell...
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02/19/2019
Towards Hardware Implementation of Neural Network-based Communication Algorithms
There is a recent interest in neural network (NN)-based communication al...
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02/11/2019
Massive MIMO is a Reality - What is Next? Five Promising Research Directions for Antenna Arrays
Massive MIMO (multiple-input multiple-output) is no longer a "wild" or "...
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01/08/2019
Enabling FDD Massive MIMO through Deep Learning-based Channel Prediction
A major obstacle for widespread deployment of frequency division duplex ...
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12/14/2018
Model-free Training of End-to-end Communication Systems
The idea of end-to-end learning of communication systems through neural ...
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11/08/2018
Fundamental Asymptotic Behavior of (Two-User) Distributed Massive MIMO
This paper considers the uplink of a distributed Massive MIMO network wh...
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11/05/2018
Hardware Distortion Correlation Has Negligible Impact on UL Massive MIMO Spectral Efficiency
This paper analyzes how the distortion created by hardware impairments i...
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10/12/2018
Deep Reinforcement Learning Autoencoder with Noisy Feedback
End-to-end learning of communication systems enables joint optimization ...
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07/02/2018
Online Label Recovery for Deep Learning-based Communication through Error Correcting Codes
We demonstrate that error correcting codes (ECCs) can be used to constru...
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05/21/2018
Can Hardware Distortion Correlation be Neglected When Analyzing Uplink SE in Massive MIMO?
This paper analyzes how the distortion created by hardware impairments i...
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04/06/2018
End-to-End Learning of Communications Systems Without a Channel Model
The idea of end-to-end learning of communications systems through neural...
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03/15/2018
OFDM-Autoencoder for End-to-End Learning of Communications Systems
We extend the idea of end-to-end learning of communications systems thro...
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07/11/2017