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Molecular Communications and Nanonetworks

#41045, Summer 2023



Welcome to the amazing world of nanonetworks, where chemistry, physics, and communication networks confluence together. The new approaches in the nanodomain covered in this course will introduce you to the most actual research and applications in the molecular communication field. Ready to navigate non-conventional topics and learn new principles beyond RF communications?

Contents

random walk figure This course will cover communication techniques and technologies to conceive networks on the nanoscale. Instead of the standard use of electromagnetic waves, communication will be achieved through the emission and detection of molecules according to the paradigm of Molecular Communications. We will follow a network architecture approach from a computer networks perspective. In the physical layer, we will introduce models for the communication channels through molecular means, as well as for emitters and receivers. In the link layer, we will address mechanisms for the information flow and error control mechanisms. The course will conduct various hands-on activities in the Matlab simulator for the modeling of the physical and link layers.

Learning Outcome

After completing the course, the attendees will characterize main communication schemes in molecular scenarios. Besides, they will apply theoretical knowledge to develop molecular communication networks. Finally, students will be able to develop molecular communication links with simulators.

Course details

Course content This master course will be held in English and all the course material is available in English. For more information, slides, and required submissions, please see our ISIS page.

      The course is organized in 16 Sessions aiming to follow the topics

      Topics

      Instructors

      Schedule

      • Lessons
        Wednesday, 14:00-16:00h (c.t.), HFT-TA 340
      • Labs
        Thursday, 14:00-16:00h (c.t.), HFT-TA 341

      Literature

      • Tadashi Nakano, Andrew W. Eckford and Tokuko Haraguchi, Molecular Communication, Cambridge University Press, 2013. [DOI, BibTeX, Details...]
      • Howard C. Berg, Random Walks in Biology, Princeton University Press, 1993. [BibTeX, Details...]
      • Vahid Jamali, Arman Ahmadzadeh, Wayan Wicke, Adam Noel and Robert Schober, "Channel Modeling for Diffusive Molecular Communication - A Tutorial Review," Proceedings of the IEEE, vol. 107 (7), pp. 1256–1301, July 2019. [DOI, BibTeX, Details...]
      • Mehmet Sukru Kuran, H. Birkan Yilmaz, Ilker Demirkol, Nariman Farsad and Andrea Goldsmith, "A Survey on Modulation Techniques in Molecular Communication via Diffusion," IEEE Communications Surveys & Tutorials, vol. 23 (1), pp. 7–28, January 2021. [DOI, BibTeX, Details...]
      • Jean Philibert, "One and a Half Century of Diffusion: Fick, Einstein, Before and Beyond," The Open-Access Journal for the Basic Principles of Diffusion Theory, Experiment and Application, vol. 4, pp. 1–19, 2006. [BibTeX, Details...]
      • Luca Felicetti, Mauro Femminella, Gianluca Reali, Tadashi Nakano and Athanasios V Vasilakos, "TCP-Like Molecular Communications," IEEE Journal on Selected Areas in Communications (JSAC), vol. 32 (12), pp. 2354–2367, December 2014. [DOI, BibTeX, Details...]
      • Baris Atakan and Ozgur B. Akan, "On Channel Capacity and Error Compensation in Molecular Communication," in Springer Transactions on Computational Systems Biology X, Biological and Biologically-inspired Communication, vol. LNBI 5410, Corrado Priami, Falko Dressler, Ozgur B. Akan and Alioune Ngom (Eds.), Springer, 2008, pp. 59–80. [DOI, BibTeX, Details...]
      • Tadashi Nakano, "Molecular Communication: A 10 Year Retrospective," IEEE Transactions on Molecular, Biological and Multi-Scale Communications (T-MBMC), vol. 3 (2), pp. 71–78, June 2017. [DOI, BibTeX, Details...]
      • Tadashi Nakano, Tatsuya Suda, Y. Okaie, M. J. Moore and A. V. Vasilakos, "Molecular Communication Among Biological Nanomachines: A Layered Architecture and Research Issues," IEEE Transactions on NanoBioscience, vol. 13 (3), pp. 169–197, September 2014. [DOI, BibTeX, Details...]
      • Steven Kay, Fundamentals of Statistical Signal Processing: Estimation Theory, Prentice Hall, 1998. [BibTeX, Details...]

Extras

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