Project P9
P9: Theoretical Modelling, Design, and Analysis of Olfaction-inspired Molecule-Mixture Communications
Motivation and state of the art:
Motivated by natural olfaction (as the most prominent form of airborne MCs in nature), various bio-inspired transmitter and receiver designs are proposed in P7 and P8, respectively, to realize synthetic airborne MC systems. Thereby, odor objects (also referred to as odor codes or mixture codes) are used as information carriers where each odor object is typically a mixture of different types of molecules and is used to represent a particular message. The design of an efficient airborne molecule-mixture communication system involves several challenges including (i) robust delivery and detection of molecule-mixture signals, (ii) optimized choice of relevant generalist and specialist sensors for a scalable receiver architecture for molecule-mixture detection, (iii) optimization of the geometrical arrangement of release and reception sites, and (iv) resilience of the aforementioned designs in the presence of uncertainty due to, e.g., transmitter and/or receiver mobility and fluctuating background odors. Rigorous treatment of the considerations in (i)-(iv) requires an in-depth understanding of the mechanisms involved in the release, propagation, and detection of molecule mixtures and translating them into communication-theoretical models that can be subsequently used for developing communication techniques and algorithms (e.g., for modulation and detection). With the exception of our preliminary work in 1 , which investigates cross-reactive receptor array (CRRA) architectures for molecule-mixture detection, the models and communication strategies developed so far for synthetic MC systems2-8 do not account for the peculiarities and features of olfaction-inspired molecule-mixture communication summarized in (i)-(iv). Moreover, while natural and synthetic olfaction has been an active area of research in the past decades in bio-chemistry9,10, synthetic biology11,12, cognitive processing13,14, and sensor technology12,15,16, exploiting olfaction as an enabler for synthetic airborne MC, modelling and understanding it from a communication-theoretical perspective, and optimizing it for efficient communication have not been a focus of the existing literature.
Objectives:
The main objectives of this project are: (i) Communication-theoretical modelling of the end-to-end molecule-mixture communication systems studied in P7 and P8 including the release, propagation, and reception processes, (ii) design of communication techniques and algorithms for molecule-mixture communication such as the construction of the mixture alphabet used for modulation and the development of detection schemes for the recovery of molecule-mixture encoded data from the sensor array signal, (iii) system optimization based on the developed communication models and algorithms including optimization of the constituents of molecule mixtures, design of the release mode and the geometric arrangements of the release sites at the transmitter, and investigation of favorable components and geometrical arrangements of receiver sensor arrays, and (iv) verification and/or refinement of the developed models, designs, and analysis using measurement data collected in P7 and P8. The models and designs developed in this project will account for the key constraints of the practical airborne MC systems studied in P7 and P8 and will be continuously refined based on measurement results. On the other hand, the obtained theoretical results will guide the experiments in P7 and P8 and help determine, e.g., favorable mixture compositions, release modes, and geometrical arrangements of release and sensing sites.
References
1.Jamali, H. Loos, A. Buettner, J. Pillow, R. Schober, and V. Poor, “Olfaction-inspired MCs: Molecule Mixture Shift Keying and Cross-reactive Receptor Arrays,” IEEE Trans. Commun., vol. 71, no. 4, pp. 1894-1911, Apr. 2023.
2.Söldner, E. Socher, V. Jamali, W. Wicke, A. Ahmadzadeh, H. Breitinger, A. Burkovski, K. Castiglione, R. Schober, and H. Sticht. “A Survey of Biological Building Blocks for Synthetic Molecular Communication Systems”. IEEE Commun. Surv. Tutor., vol. 22, pp. 2765-2800, Fourthquarter 2020.
3.V. Jamali, A. Ahmadzadeh, W. Wicke, A. Noel, and R. Schober. Channel Modeling for Diffusive Molecular Communication—A Tutorial Review, Proc. IEEE, vol. 107, pp. 1256-1301, Jul. 2019.
4.Farsad, B. Yilmaz, A. Eckford, C. Chae, and W. Guo. “A Comprehensive Survey of Recent Advances in Molecular Communication,” IEEE Commun. Surv. Tutor., vol. 18, pp. 1887-1919, Thirdquarter 2016.
5.S. Bhattacharjee, M. Damrath, F. Bronner, L. Stratmann, J. Drees, F. Dressler, and P. Hoeher, “A Testbed and Simulation Framework for Air-based Molecular Communication using Fluorescein,” in Proc. 7th ACM Int. Conf. Nanosc. Comp. Commun., pp. 1-6, 2020.
6.Atakan, O. Akan, and S. Balasubramaniam, „Body Area Nanonetworks with Molecular Communications in Nanomedicine,“ IEEE Commun. Mag., vol. 50, pp. 28-34, Jan. 2012.
7.McGuiness, et al., „Analysis of Multi-chemical Transmission in the Macro-scale,“ IEEE Trans. Mol. Biol. Multi-Scale Commun., vol. 6, pp. 93-106, Nov. 2020.
8.Damrath, S. Bhattacharjee, and P. Hoeher, „Investigation of Multiple Fluorescent Dyes in Macroscopic Air-Based Molecular Communication,“ IEEE Trans. Mol. Biol. Multi-Scale Commun., vol. 7, pp. 78-82, Jun. 2021.
9.Zufall and T. Leinders-Zufall, “The Cellular and Molecular Basis of Odor Adaptation,” Chemical Senses, vol. 25, no. 4, pp. 473–481, 2000.
10.Hallem, M. Ho, and J. Carlson, “The Molecular Basis of Odor Coding in the Drosophila Antenna,” Cell, vol. 117, no. 7, pp. 965–979, 2004.
11.Barbosa, A. Oliveira, and A. Roque, “Protein-and Peptide-based Biosensors in Artificial Olfaction,” Trends Biotechnol., vol. 36, no. 12, pp. 1244–1258, 2018.
12.Dung, Y. Oh, S.-J. Choi, I.-D. Kim, M.-K. Oh, and M. Kim, “Applications and Advances in Bioelectronic Noses for Odour Sensing,” Sensors, vol. 18, 2018, doi: 10.3390/s18010103.
13.Thomas-Danguin, C. Sinding, S. Romagny, F. El Mountassir, B. Atanasova, E. Le Berre, A.-M. Le Bon, and G. Coureaud, “The Perception of Odor Objects in Everyday Life: A Review on the Processing of Odor Mixtures,” Front. Psychol., vol. 5, 2014, doi: 10.3389/fpsyg.2014.00504.
14.J. Freiherr, „Cortical Olfactory Processing,“ Springer Handbook of Odor, Springer, Cham, pp. 97-98, 2017.
15.T. Pearce, S. Schiffman, H. Nagle, J. Gardner (Eds.). Handbook of Machine Olfaction: Electronic Nose Technology, Wiley, 2003.
16.Pelosi, J. Zhu, and W. Knoll, “From Gas Sensors to Biomimetic Artificial Noses,” Chemosensors, vol. 6, 2018, doi: 10.3390/chemosensors6030032.