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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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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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Towards a 6G AI-Native Air Interface
Each generation of cellular communication systems is marked by a definin...
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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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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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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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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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Deep HyperNetwork-Based MIMO Detection
Optimal symbol detection for multiple-input multiple-output (MIMO) syste...
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Trainable Communication Systems: Concepts and Prototype
We consider a trainable point-to-point communication system, where both ...
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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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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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"Machine LLRning": Learning to Softly Demodulate
Soft demodulation, or demapping, of received symbols back into their con...
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Joint Learning of Geometric and Probabilistic Constellation Shaping
The choice of constellations largely affects the performance of communic...
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Adaptive Neural Signal Detection for Massive MIMO
Symbol detection for Massive Multiple-Input Multiple-Output (MIMO) is a ...
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Transmitter Classification With Supervised Deep Learning
Hardware imperfections in RF transmitters introduce features that can be...
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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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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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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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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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Enabling FDD Massive MIMO through Deep Learning-based Channel Prediction
A major obstacle for widespread deployment of frequency division duplex ...
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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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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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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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Deep Reinforcement Learning Autoencoder with Noisy Feedback
End-to-end learning of communication systems enables joint optimization ...
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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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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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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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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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Deep Learning-Based Communication Over the Air
End-to-end learning of communications systems is a fascinating novel con...
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