Luca Rose
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View article: OLIVANDER: a counterfactual-based method to generate adversarial Windows PE malware
OLIVANDER: a counterfactual-based method to generate adversarial Windows PE malware Open
Artificial Intelligence (AI) is transforming cybersecurity practices thanks to the amazing accuracy performance achieved with several AI-based malware detection systems. However, several recent studies have shown that AI decision models ca…
View article: VINCENT: Cyber-threat detection through vision transformers and knowledge distillation
VINCENT: Cyber-threat detection through vision transformers and knowledge distillation Open
Vision Transformers (ViTs) denote a family of attention-based deep learning techniques that have recently achieved amazing results in various problems related to the field of computer vision. In this paper, we explore the use of ViTs in pr…
View article: Massive MIMO CSI Feedback Using Channel Prediction: How to Avoid Machine Learning at UE?
Massive MIMO CSI Feedback Using Channel Prediction: How to Avoid Machine Learning at UE? Open
In the literature, machine learning (ML) has been implemented at the base\nstation (BS) and user equipment (UE) to improve the precision of downlink\nchannel state information (CSI). However, ML implementation at the UE can be\ninfeasible …
View article: Design of an Efficient CSI Feedback Mechanism in Massive MIMO Systems: A Machine Learning Approach using Empirical Data
Design of an Efficient CSI Feedback Mechanism in Massive MIMO Systems: A Machine Learning Approach using Empirical Data Open
Massive multiple-input multiple-output (mMIMO) regime reaps the benefits of spatial diversity and multiplexing gains, subject to precise channel state information (CSI) acquisition. In the current communication architecture, the downlink C…
View article: Real-Time Massive MIMO Channel Prediction: A Combination of Deep Learning and NeuralProphet
Real-Time Massive MIMO Channel Prediction: A Combination of Deep Learning and NeuralProphet Open
Channel state information (CSI) is of pivotal importance as it enables wireless systems to adapt transmission parameters more accurately, thus improving the system's overall performance. However, it becomes challenging to acquire accurate …
View article: Series Editorial: Internet of Things
Series Editorial: Internet of Things Open
This first edition of the Internet of Things Series of IEEE Communications Magazine comes at a time when the world is slowly rolling back from the COVID pandemic to a possible endemic. Organizations worldwide are preparing business operati…
View article: Artificial Intelligence for 6G Networks: Technology Advancement and Standardization
Artificial Intelligence for 6G Networks: Technology Advancement and Standardization Open
With the deployment of 5G networks, standards organizations have started\nworking on the design phase for sixth-generation (6G) networks. 6G networks\nwill be immensely complex, requiring more deployment time, cost and management\nefforts.…
View article: Smart Link Adaptation and Scheduling for IIoT
Smart Link Adaptation and Scheduling for IIoT Open
International audience
View article: RNN-Based Twin Channel Predictors for CSI Acquisition in UAV-Assisted 5G+ Networks
RNN-Based Twin Channel Predictors for CSI Acquisition in UAV-Assisted 5G+ Networks Open
International audience
View article: A Novel Algorithm to Report CSI in MIMO-Based Wireless Networks
A Novel Algorithm to Report CSI in MIMO-Based Wireless Networks Open
In wireless communication, accurate channel state information (CSI) is of pivotal importance. In practice, due to processing and feedback delays, estimated CSI can be outdated, which can severely deteriorate the performance of the communic…
View article: Dealing with CSI Compression to Reduce Losses and Overhead: An Artificial Intelligence Approach
Dealing with CSI Compression to Reduce Losses and Overhead: An Artificial Intelligence Approach Open
Motivated by the issue of inaccurate channel state information (CSI) at the base station (BS), which is commonly due to feedback/processing delays and compression problems, in this paper, we introduce a scalable idea of adopting artificial…
View article: Dealing with CSI Compression to Reduce Losses and Overhead: An\n Artificial Intelligence Approach
Dealing with CSI Compression to Reduce Losses and Overhead: An\n Artificial Intelligence Approach Open
Motivated by the issue of inaccurate channel state information (CSI) at the\nbase station (BS), which is commonly due to feedback/processing delays and\ncompression problems, in this paper, we introduce a scalable idea of adopting\nartific…
View article: Uplink Beam Management for Millimeter Wave Cellular MIMO Systems with Hybrid Beamforming
Uplink Beam Management for Millimeter Wave Cellular MIMO Systems with Hybrid Beamforming Open
Hybrid analog and digital BeamForming (HBF) is one of the enabling transceiver technologies for millimeter Wave (mmWave) Multiple Input Multiple Output (MIMO) systems. This technology offers highly directional communication, which is able …
View article: Uplink Beam Management for Millimeter Wave Cellular MIMO Systems with\n Hybrid Beamforming
Uplink Beam Management for Millimeter Wave Cellular MIMO Systems with\n Hybrid Beamforming Open
Hybrid analog and digital BeamForming (HBF) is one of the enabling\ntransceiver technologies for millimeter Wave (mmWave) Multiple Input Multiple\nOutput (MIMO) systems. This technology offers highly directional communication,\nwhich is ab…
View article: Performance Assessment of MIMO Precoding on Realistic mmWave Channels
Performance Assessment of MIMO Precoding on Realistic mmWave Channels Open
In this paper, the performance of multi-user Multiple-Input Multiple-Output (MIMO) systems is evaluated in terms of SINR and capacity. We focus on the case of a downlink single-cell scenario where different precoders have been studied. Amo…
View article: Channel and Power Allocation Algorithms for Ad Hoc Clustered Networks
Channel and Power Allocation Algorithms for Ad Hoc Clustered Networks Open
—In the context of mobile clustered ad hoc networks, this paper proposes and studies a self-configuring algorithm which is able to jointly set the channel frequency and power level of the transmitting nodes, by exploiting one bit of feedba…
View article: CORASMA Program on Cognitive Radio for Tactical Networks: High Fidelity Simulator and First Results on Dynamic Frequency Allocation
CORASMA Program on Cognitive Radio for Tactical Networks: High Fidelity Simulator and First Results on Dynamic Frequency Allocation Open
—This paper reports some preliminary results of the “cognitive radio for dynamic spectrum management” (CORASMA) program that is dedicated to the evaluation of cognitive solutions for tactical wireless networks. It presents two main aspects…