Search Results for author: Salvatore D'Oro

Found 9 papers, 3 papers with code

Intelligent Closed-loop RAN Control with xApps in OpenRAN Gym

no code implementations31 Aug 2022 Leonardo Bonati, Michele Polese, Salvatore D'Oro, Stefano Basagni, Tommaso Melodia

Softwarization, programmable network control and the use of all-encompassing controllers acting at different timescales are heralded as the key drivers for the evolution to next-generation cellular networks.

OpenRAN Gym: AI/ML Development, Data Collection, and Testing for O-RAN on PAWR Platforms

1 code implementation25 Jul 2022 Leonardo Bonati, Michele Polese, Salvatore D'Oro, Stefano Basagni, Tommaso Melodia

In this paper we present OpenRAN Gym, a unified, open, and O-RAN-compliant experimental toolbox for data collection, design, prototyping and testing of end-to-end data-driven control solutions for next generation Open RAN systems.

Neural Network-based OFDM Receiver for Resource Constrained IoT Devices

no code implementations12 May 2022 Nasim Soltani, Hai Cheng, Mauro Belgiovine, Yanyu Li, Haoqing Li, Bahar Azari, Salvatore D'Oro, Tales Imbiriba, Tommaso Melodia, Pau Closas, Yanzhi Wang, Deniz Erdogmus, Kaushik Chowdhury

Here, ML blocks replace the individual processing blocks of an OFDM receiver, and we specifically describe this swapping for the legacy channel estimation, symbol demapping, and decoding blocks with Neural Networks (NNs).

Quantization

OrchestRAN: Network Automation through Orchestrated Intelligence in the Open RAN

no code implementations14 Jan 2022 Salvatore D'Oro, Leonardo Bonati, Michele Polese, Tommaso Melodia

The next generation of cellular networks will be characterized by softwarized, open, and disaggregated architectures exposing analytics and control knobs to enable network intelligence.

Scheduling

ColO-RAN: Developing Machine Learning-based xApps for Open RAN Closed-loop Control on Programmable Experimental Platforms

1 code implementation17 Dec 2021 Michele Polese, Leonardo Bonati, Salvatore D'Oro, Stefano Basagni, Tommaso Melodia

In this paper, we address these challenges by proposing practical solutions and software pipelines for the design, training, testing, and experimental evaluation of DRL-based closed-loop control in the Open RAN.

Scheduling

Can You Fix My Neural Network? Real-Time Adaptive Waveform Synthesis for Resilient Wireless Signal Classification

no code implementations5 Mar 2021 Salvatore D'Oro, Francesco Restuccia, Tommaso Melodia

Results show that Chares increases the accuracy up to 4. 1x when no waveform synthesis is performed, by 1. 9x with respect to existing work, and can compute new actions within 41us.

SteaLTE: Private 5G Cellular Connectivity as a Service with Full-stack Wireless Steganography

no code implementations10 Feb 2021 Leonardo Bonati, Salvatore D'Oro, Francesco Restuccia, Stefano Basagni, Tommaso Melodia

Differently from previous work, however, it takes a full-stack approach to steganography, contributing an LTE-compliant steganographic protocol stack for PCCaaS-based communications, and packet schedulers and operations to embed covert data streams on top of traditional cellular traffic (primary traffic).

Networking and Internet Architecture Cryptography and Security

Intelligence and Learning in O-RAN for Data-driven NextG Cellular Networks

1 code implementation2 Dec 2020 Leonardo Bonati, Salvatore D'Oro, Michele Polese, Stefano Basagni, Tommaso Melodia

Next Generation (NextG) cellular networks will be natively cloud-based and built upon programmable, virtualized, and disaggregated architectures.

Scheduling

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