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Colosseum, the world's largest wireless network emulator

Published: 25 October 2021 Publication History
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  • Abstract

    Practical experimentation and prototyping are core steps in the development of any wireless technology. Often times, however, this crucial step is confined to small laboratory setups that do not capture the scale of commercial deployments and do not ensure result reproducibility and replicability, or it is skipped altogether for lack of suitable hardware and testing facilities. Recent years have seen the development of publicly-available testing platforms for wireless experimentation at scale. Examples include the testbeds of the PAWR program and Colosseum, the world's largest wireless network emulator. With its 256 software-defined radios, 24 racks of powerful compute servers and first-of-its-kind channel emulator, Colosseum allows users to prototype wireless solutions at scale, and guarantees reproducibility and replicability of results. This tutorial provides an overview of the Colosseum platform. We describe the architecture and components of the testbed as a whole, and we then showcase how to run practical experiments in diverse scenarios with heterogeneous wireless technologies (e.g., Wi-Fi and cellular). We also emphasize how Colosseum experiments can be ported to different testing platforms, facilitating full-cycle experimental wireless research: design, experiments and tests at scale in a fully controlled and observable environment and testing in the field. The tutorial concludes with considerations on the flexible future of Colosseum, focusing on its planned extension to emulate larger scenarios and channels at higher frequency bands (mmWave).

    References

    [1]
    Leonardo Bonati, Salvatore D'Oro, Stefano Basagni, and Tommaso Melodia. 2021. SCOPE: An Open and Softwarized Prototyping Platform for NextG Systems. In Proceedings of ACM MobiSys. Virtual Conference.
    [2]
    Ashish Chaudhari and Martin Braun. 2018. A Scalable FPGA Architecture for Flexible, Large-Scale, Real-Time RF Channel Emulation. In Proceedings of IEEE ReCoSoC. Lille, France.
    [3]
    DARPA. 2016. Spectrum Collaboration Challenge. https://www.darpa.mil/program/spectrum-collaboration-challenge. Accessed September 2021.

    Cited By

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    • (2024)Reinforcement Learning-based Performance-aware Energy Management in 5G Base Stations2024 16th International Conference on COMmunication Systems & NETworkS (COMSNETS)10.1109/COMSNETS59351.2024.10427091(568-571)Online publication date: 3-Jan-2024
    • (2023)Frequency extension of radio propagation model using fine-tuningIEICE Communications Express10.1587/comex.2023XBL008012:9(499-504)Online publication date: 1-Sep-2023
    • (2023)EXPLORA: AI/ML EXPLainability for the Open RANProceedings of the ACM on Networking10.1145/36291411:CoNEXT3(1-26)Online publication date: 28-Nov-2023
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    cover image ACM Conferences
    MobiCom '21: Proceedings of the 27th Annual International Conference on Mobile Computing and Networking
    October 2021
    887 pages
    ISBN:9781450383424
    DOI:10.1145/3447993
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Publication History

    Published: 25 October 2021

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    Author Tags

    1. experimental wireless research
    2. wireless channel emulation

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    • (2024)Reinforcement Learning-based Performance-aware Energy Management in 5G Base Stations2024 16th International Conference on COMmunication Systems & NETworkS (COMSNETS)10.1109/COMSNETS59351.2024.10427091(568-571)Online publication date: 3-Jan-2024
    • (2023)Frequency extension of radio propagation model using fine-tuningIEICE Communications Express10.1587/comex.2023XBL008012:9(499-504)Online publication date: 1-Sep-2023
    • (2023)EXPLORA: AI/ML EXPLainability for the Open RANProceedings of the ACM on Networking10.1145/36291411:CoNEXT3(1-26)Online publication date: 28-Nov-2023
    • (2023)Where Are The (Cellular) Data?ACM Computing Surveys10.1145/3610402Online publication date: 20-Jul-2023
    • (2023)RNN-Based Path Loss Modeling with Variable-Size Map Data in Urban Environments2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring)10.1109/VTC2023-Spring57618.2023.10199449(1-5)Online publication date: Jun-2023
    • (2023)Millimeter Wave Path Loss Modeling using Multi-Resolution Map Based on ResNet2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall)10.1109/VTC2023-Fall60731.2023.10333759(1-5)Online publication date: 10-Oct-2023
    • (2022)Fine-Tuning for Propagation Modeling of Different Frequencies with Few Data2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)10.1109/VTC2022-Fall57202.2022.10012911(1-5)Online publication date: Sep-2022
    • (2022)A Study on Path Loss Modeling using ResNet and Pre-Training with Free Space Path Loss2022 IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)10.1109/PIMRC54779.2022.9977760(01-05)Online publication date: 12-Sep-2022
    • (2022)Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks2022 IEEE 8th International Conference on Collaboration and Internet Computing (CIC)10.1109/CIC56439.2022.00013(16-25)Online publication date: Dec-2022

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