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08/04/2023
Universal Approximation of Linear Time-Invariant (LTI) Systems through RNNs: Power of Randomness in Reservoir Computing
Recurrent neural networks (RNNs) are known to be universal approximators...
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03/13/2023
5G-Advanced Towards 6G: Past, Present, and Future
Since the start of 5G work in 3GPP in early 2016, tremendous progress ha...
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03/02/2023
A Tutorial on AI-Enabled Non-Terrestrial Networks in 6G
Non-Terrestrial Networks (NTN) are expected to be a critical component o...
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03/02/2023
Distributed Learning Meets 6G: A Communication and Computing Perspective
With the ever-improving computing capabilities and storage capacities of...
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08/17/2022
Learn to Detect and Detect to Learn: Structure Learning and Decision Feedback for MIMO-OFDM Receive Processing
One of the major open challenges in MIMO-OFDM receive processing is how ...
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12/22/2021
Efficient Data Exchange in Unmanned Aerial Vehicle Networks Utilizing Unsupervised Learning-Based Clustering
An unmanned aerial vehicle (UAV) network can serve as an aerial relay to...
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11/09/2021
Optimizing Number, Placement, and Backhaul Connectivity of Multi-UAV Networks
Multi-Unmanned Aerial Vehicle (UAV) Networks is a promising solution to ...
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10/03/2021
RC-Struct: A Structure-based Neural Network Approach for MIMO-OFDM Detection
In this paper, we introduce a structure-based neural network architectur...
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06/28/2021
Federated Dynamic Spectrum Access
Due to the growing volume of data traffic produced by the surge of Inter...
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06/06/2021
Adversarial Classification of the Attacks on Smart Grids Using Game Theory and Deep Learning
Smart grids are vulnerable to cyber-attacks. This paper proposes a game-...
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02/27/2021
Towards Intelligent RAN Slicing for B5G: Opportunities and Challenges
To meet the diverse demands for wireless communication, fifth-generation...
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02/06/2021
Making Intelligent Reflecting Surfaces More Intelligent: A Roadmap Through Reservoir Computing
This article introduces a neural network-based signal processing framewo...
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01/28/2021
Differential Privacy Meets Federated Learning under Communication Constraints
The performance of federated learning systems is bottlenecked by communi...
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12/21/2020
To Talk or to Work: Energy Efficient Federated Learning over Mobile Devices via the Weight Quantization and 5G Transmission Co-Design
Federated learning (FL) is a new paradigm for large-scale learning tasks...
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12/02/2020
Pareto Deterministic Policy Gradients and Its Application in 5G Massive MIMO Networks
In this paper, we consider jointly optimizing cell load balance and netw...
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12/01/2020
Learning with Knowledge of Structure: A Neural Network-Based Approach for MIMO-OFDM Detection
In this paper, we explore neural network-based strategies for performing...
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11/10/2020
Learning for Integer-Constrained Optimization through Neural Networks with Limited Training
In this paper, we investigate a neural network-based learning approach t...
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10/12/2020
Deep Echo State Q-Network (DEQN) and Its Application in Dynamic Spectrum Sharing for 5G and Beyond
Deep reinforcement learning (DRL) has been shown to be successful in man...
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07/15/2020
Federated Learning in Mobile Edge Computing: An Edge-Learning Perspective for Beyond 5G
Owing to the large volume of sensed data from the enormous number of IoT...
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04/30/2020
Delay-aware Resource Allocation in Fog-assisted IoT Networks Through Reinforcement Learning
Fog nodes in the vicinity of IoT devices are promising to provision low ...
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03/15/2020
RCNet: Incorporating Structural Information into Deep RNN for MIMO-OFDM Symbol Detection with Limited Training
In this paper, we investigate learning-based MIMO-OFDM symbol detection ...
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09/15/2019
CogRF: A New Frontier for Machine Learning and Artificial Intelligence for 6G RF Systems
The concept of CogRF, a novel tunable radio frequency (RF) frontend that...
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07/18/2019
Artificial Intelligence-Enabled Cellular Networks: A Critical Path to Beyond-5G and 6G
Mobile Network Operators (MNOs) are in process of overlaying their conve...
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06/25/2019
Learn to Demodulate: MIMO-OFDM Symbol Detection through Downlink Pilots
Reservoir computing (RC) is a special neural network which consists of a...
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06/14/2019
Self-Tuning Sectorization: Deep Reinforcement Learning Meets Broadcast Beam Optimization
Beamforming in multiple input multiple output (MIMO) systems is one of t...
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10/29/2018
Big Data Meet Cyber-Physical Systems: A Panoramic Survey
The world is witnessing an unprecedented growth of cyber-physical system...
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10/28/2018
Distributive Dynamic Spectrum Access through Deep Reinforcement Learning: A Reservoir Computing Based Approach
Dynamic spectrum access (DSA) is regarded as an effective and efficient ...
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09/26/2018
