If you use Colosseum for your research, please cite the following paper:

L. Bonati, P. Johari, M. Polese, S. D’Oro, S. Mohanti, M. Tehrani-Moayyed, D. Villa, S. Shrivastava, C. Tassie, K. Yoder, A. Bagga, P. Patel, V. Petkov, M. Seltser, F. Restuccia, A. Gosain, K.R. Chowdhury, S. Basagni, T. Melodia, “Colosseum: Large-Scale Wireless Experimentation Through Hardware-in-the-Loop Network Emulation,” in Proceedings of IEEE Intl. Symp. on Dynamic Spectrum Access Networks (DySPAN), Virtual Conference, December 2021. [pdf] [bibtex]

Colosseum has been featured in the following publications:

  • S. D’Oro, L. Bonati, M. Polese, T. Melodia, “OrchestRAN: Network Automation through Orchestrated Intelligence in the Open RAN,” in Proceedings of IEEE INFOCOM, May 2022. [pdf] [bibtex]
  • L. Baldesi, F. Restuccia, T. Melodia, “ChARM: NextG Spectrum Sharing Through Data-Driven Real-Time O-RAN Dynamic Control,” in Proceedings of IEEE INFOCOM, May 2022. [pdf] [bibtex]
  • L. Bonati, M. Polese, S. D’Oro, S. Basagni, T. Melodia, “OpenRAN Gym: An Open Toolbox for Data Collection and Experimentation with AI in O-RAN,” Proc. of IEEE WCNC Workshop on Open RAN Architecture for 5G Evolution and 6G, Austin, TX, USA, April 2022. [pdf] [bibtex]
  • M. Polese, L. Bonati, S. D’Oro, S. Basagni, T. Melodia, “ColO-RAN: Developing Machine Learning-based xApps for Open RAN Closed-loop Control on Programmable Experimental Platforms,” arXiv:2112.09559 [cs.NI]. [pdf] [bibtex]
  • L. Bonati, P. Johari, M. Polese, S. D’Oro, S. Mohanti, M. Tehrani-Moayyed, D. Villa, S. Shrivastava, C. Tassie, K. Yoder, A. Bagga, P. Patel, V. Petkov, M. Seltser, F. Restuccia, A. Gosain, K.R. Chowdhury, S. Basagni, T. Melodia, “Colosseum: Large-Scale Wireless Experimentation Through Hardware-in-the-Loop Network Emulation,” in Proceedings of IEEE Intl. Symp. on Dynamic Spectrum Access Networks (DySPAN), Virtual Conference, December 2021. [pdf] [bibtex]
  • L. Bonati, S. D’Oro, M. Polese, S. Basagni, and T. Melodia, “Intelligence and Learning in O-RAN for Data-driven NextG Cellular Networks,” IEEE Communications Magazine, vol. 59, no. 10, pp. 21–27, October 2021. [pdf] [bibtex]
  • T. Melodia, S. Basagni, K.R. Chowdhury, A. Gosain, M. Polese, P. Johari, and L. Bonati, “Tutorial: Colosseum, the World’s Largest Wireless Network Emulator,” in Proceedings of ACM MobiCom, New Orleans, LA, USA, October 2021. [pdf] [bibtex]
  • B. Casasole, L. Bonati, S. D’Oro, S. Basagni, A. Capone, and T. Melodia, “QCell: Self-optimization of Softwarized 5G Networks through Deep Q-learning,” in Proceedings of IEEE GLOBECOM, Madrid, Spain, December 2021. [pdf] [bibtex]
  • J.M. Shea, T.F. Wong, “A Deep Q-Learning Dynamic Spectrum Sharing Experiment,” in Proceedings of IEEE ICC, Montreal, QC, Canada, August 2021. [link]
  • L. Bonati, S. D’Oro, S. Basagni, and T. Melodia, “SCOPE: An Open and Softwarized Prototyping Platform for NextG Systems,” in Proceedings of ACM MobiSys, Virtual Conference, June 2021. [pdf] [bibtex]
  • M. Tehrani-Moayyed, L. Bonati, P. Johari, T. Melodia, and S. Basagni, “Creating RF Scenarios for Large-Scale, Real-Time Wireless Channel Emulators,” in Proceedings of IEEE Mediterranean Communication and Computer Networking Conference (MedComNet), Virtual Conference, June 2021. [pdf] [bibtex]
  • M. Camelo, A. Shahid, J. Fontaine, F. A. Pereira de Figueiredo, E. De Poorter, I. Moerman, S. Latre, “A Semi-supervised Learning Approach towards Automatic Wireless Technology Recognition,” in Proceedings of IEEE DySPAN, Newark, NJ, USA, November 2019. [link]
  • P. Tilghman, “AI Will Rule the Airwaves: A DARPA Grand Challenge Seeks Autonomous Radios to Manage the Wireless Spectrum,” IEEE Spectrum, vol. 56, no. 6, pp. 28–33, May 2019.
  • R. L. Yuan and K. M. Schmidt, “Defense Advanced Research Projects Agency Spectrum Collaboration Challenge at APL: Introduction,” vol. 35, no. 1, pp. 2–3, 2019.
  • D. Coleman et al., “Overview of the Colosseum: The World’s Largest Test Bed for Radio Experiments,” Johns Hopkins APL Technical Digest, vol. 35, no. 1, pp. 4–11, 2019.
  • A. S. Freeman et al., “Software Project Management for the Defense Advanced Research Projects Agency Spectrum Collaboration Challenge,” Johns Hopkins APL Technical Digest, vol. 35, no. 1, pp. 12–21, 2019.
  • A. T. Plummer, Jr. and K. P. Taylor, “Development and Operations on the Defense Advanced Research Project Agency’s Spectrum Collaboration Challenge,” Johns Hopkins APL Technical Digest, vol. 35, no. 1, pp. 22– 33, 2019.
  • J. W. Mok, A. L. Hom, J. J. Uher, and D. M. Coleman, “The Resource Manager for the Defense Advanced Research Projects Agency Spectrum Collaboration Challenge Test Bed,” Johns Hopkins APL Technical Digest, vol. 35, no. 1, pp. 34–41, 2019.
  • D. A. White, Jr., J. E. Annis, and F. F. Johnson, “Standard Radio Nodes in the Defense Advanced Research Projects Agency Spectrum Collaboration Challenge,” vol. 35, no. 1, pp. 42–48, 2019.
  • K. J. Yim, K. R. McKeever, and D. R. Barcklow, “Incumbent Radio Systems in the Defense Advanced Research Projects Agency Spectrum Collaboration Challenge Test Bed,” vol. 35, no. 1, pp. 49–57, 2019.
  • P. D. Curtis, A. T. Plummer, Jr., J. E. Annis, andW. J. La Cholter, “Traffic Generation System for the Defense Advanced Research Projects Agency Spectrum Collaboration Challenge,” Johns Hopkins APL Technical Digest, vol. 35, no. 1, pp. 58–68, 2019.
  • D. Barcklow et al., “Radio Frequency Emulation System for the Defense Advanced Research Projects Agency Spectrum Collaboration Challenge,” Johns Hopkins APL Technical Digest, vol. 35, no. 1, pp. 69–78, 2019.