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Energy Allocation for Multi-User Cooperative Molecular Communication Systems in the Internet of Bio-Nano Things (2404.02286v1)

Published 2 Apr 2024 in cs.IT, eess.SP, and math.IT

Abstract: Cooperative molecular communication (MC) is a promising technology for facilitating communication between nanomachines in the Internet of Bio-Nano Things (IoBNT) field. However, the performance of IoBNT is limited by the availability of energy for cooperative MC. This paper presents a novel transmitter design scheme that utilizes molecule movement between reservoirs, creating concentration differences through the consumption of free energy, and encoding information on molecule types. The performance of the transmitter is primarily influenced by energy costs, which directly impact the overall IoBNT system performance. To address this, the paper focuses on optimizing energy allocation in cooperative MC for enhanced transmitter performance. Theoretical analysis is conducted for two transmitters. For scenarios with more than two users, a genetic algorithm is employed in the energy allocation to minimize the total bit error rate (BER). Finally, numerical results show the effectiveness of the proposed energy allocation strategies in the considered cooperative MC system.

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References (35)
  1. I. F. Akyildiz, M. Pierobon, S. Balasubramaniam, and Y. Koucheryavy, “The internet of bio-nano things,” IEEE Communications Magazine, vol. 53, no. 3, pp. 32–40, 2015.
  2. M. Kuscu and O. B. Akan, “The internet of molecular things based on fret,” IEEE Internet of Things Journal, vol. 3, no. 1, pp. 4–17, 2015.
  3. K. Aghababaiyan, H. Kebriaei, V. Shah-Mansouri, B. Maham, and D. Niyato, “Enhanced modulation for multiuser molecular communication in internet of nano things,” IEEE Internet of Things Journal, vol. 9, no. 20, pp. 19 787–19 802, 2022.
  4. L. Kong, L. Huang, L. Lin, Z. Zheng, Y. Li, Q. Wang, and G. Liu, “A survey for possible technologies of micro/nanomachines used for molecular communication within 6g application scenarios,” IEEE Internet of Things Journal, vol. 10, no. 13, pp. 11 240–11 263, 2023.
  5. N. A. Ali and M. Abu-Elkheir, “Internet of nano-things healthcare applications: Requirements, opportunities, and challenges,” in 2015 IEEE 11th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob).   IEEE, 2015, pp. 9–14.
  6. M. M. Al-Zubi, A. S. Mohan, P. Plapper, and S. H. Ling, “Intrabody molecular communication via blood-tissue barrier for internet of bio-nano things,” IEEE Internet of Things Journal, vol. 9, no. 21, pp. 21 802–21 810, 2022.
  7. H. Khoshfekr Rudsari, M. Zoofaghari, M. Veletić, J. Bergsland, and I. Balasingham, “The end-to-end molecular communication model of extracellular vesicle-based drug delivery,” IEEE Transactions on NanoBioscience, vol. 22, no. 3, pp. 498–510, 2023.
  8. L. Chouhan and M.-S. Alouini, “Interfacing of molecular communication system with various communication systems over internet of every nano things,” IEEE Internet of Things Journal, 2023.
  9. Y. Tang, Y. Huang, C.-B. Chae, W. Duan, M. Wen, and L.-L. Yang, “Molecular-type permutation shift keying in molecular mimo communications for iobnt,” IEEE Internet of Things Journal, vol. 8, no. 21, pp. 16 023–16 034, 2021.
  10. G. Yaylali, B. C. Akdeniz, T. Tugcu, and A. E. Pusane, “Channel modeling for multi-receiver molecular communication systems,” IEEE Transactions on Communications, 2023.
  11. M. S. Kuran, H. B. Yilmaz, T. Tugcu, and I. F. Akyildiz, “Modulation techniques for communication via diffusion in nanonetworks,” in 2011 IEEE international conference on communications (ICC).   IEEE, 2011, pp. 1–5.
  12. M. Ş. Kuran, H. B. Yilmaz, T. Tugcu, and I. F. Akyildiz, “Interference effects on modulation techniques in diffusion based nanonetworks,” Nano Communication Networks, vol. 3, no. 1, pp. 65–73, 2012.
  13. A. W. Eckford, “Nanoscale communication with brownian motion,” in 2007 41st Annual Conference on Information Sciences and Systems.   IEEE, 2007, pp. 160–165.
  14. Y. Fang, A. Noel, N. Yang, A. W. Eckford, and R. A. Kennedy, “Distributed cooperative detection for multi-receiver molecular communication,” in 2016 IEEE Global Communications Conference (GLOBECOM).   IEEE, 2016, pp. 1–7.
  15. N. Tavakkoli, P. Azmi, and N. Mokari, “Optimal positioning of relay node in cooperative molecular communication networks,” IEEE Transactions on Communications, vol. 65, no. 12, pp. 5293–5304, 2017.
  16. R. Mosayebi, V. Jamali, N. Ghoroghchian, R. Schober, M. Nasiri-Kenari, and M. Mehrabi, “Cooperative abnormality detection via diffusive molecular communications,” IEEE Transactions on Nanobioscience, vol. 16, no. 8, pp. 828–842, 2017.
  17. S. Dhok, L. Chouhan, A. Noel, and P. K. Sharma, “Cooperative molecular communication in drift-induced diffusive cylindrical channel,” IEEE Transactions on Molecular, Biological and Multi-Scale Communications, vol. 8, no. 1, pp. 44–55, 2021.
  18. Y. Fang, A. Noel, N. Yang, A. W. Eckford, and R. A. Kennedy, “Symbol-by-symbol maximum likelihood detection for cooperative molecular communication,” IEEE Transactions on Communications, vol. 67, no. 7, pp. 4885–4899, 2019.
  19. M. Ferrari, F. Vakilipoor, E. Regonesi, M. Rapisarda, and M. Magarini, “Channel characterization of diffusion-based molecular communication with multiple fully-absorbing receivers,” IEEE Transactions on Communications, vol. 70, no. 5, pp. 3006–3019, 2022.
  20. N. V. Sabu, A. K. Gupta, N. Varshney, and A. Jindal, “Channel characterization and performance of a 3-d molecular communication system with multiple fully-absorbing receivers,” IEEE Transactions on Communications, vol. 71, no. 2, pp. 714–727, 2022.
  21. X. Chen, M. Wen, C.-B. Chae, L.-L. Yang, F. Ji, and K. K. Igorevich, “Resource allocation for multiuser molecular communication systems oriented to the internet of medical things,” IEEE Internet of Things Journal, vol. 8, no. 21, pp. 15 939–15 952, 2021.
  22. F. Vakilipoor, A. N. Ansari, and M. Magarini, “Localizing the unknown receiver in a diffusive simo molecular communication system,” IEEE Transactions on Molecular, Biological and Multi-Scale Communications, vol. 9, no. 1, pp. 18–22, 2023.
  23. Y. Miao, W. Zhang, and X. Bao, “Levenberg–marquardt method-based cooperative source localization in simo molecular communication via diffusion systems,” IEEE Transactions on Molecular, Biological and Multi-Scale Communications, vol. 8, no. 4, pp. 229–238, 2022.
  24. N. Farsad, H. B. Yilmaz, A. Eckford, C.-B. Chae, and W. Guo, “A comprehensive survey of recent advancements in molecular communication,” IEEE Communications Surveys & Tutorials, vol. 18, no. 3, pp. 1887–1919, 2016.
  25. M. Kuscu, E. Dinc, B. A. Bilgin, H. Ramezani, and O. B. Akan, “Transmitter and receiver architectures for molecular communications: A survey on physical design with modulation, coding, and detection techniques,” Proceedings of the IEEE, vol. 107, no. 7, pp. 1302–1341, 2019.
  26. D. Demiray, A. Cabellos-Aparicio, E. Alarcón, D. T. Altilar, I. Llatser, L. Felicetti, G. Reali, and M. Femminella, “Direct: A model for molecular communication nanonetworks based on discrete entities,” Nano Communication Networks, vol. 4, no. 4, pp. 181–188, 2013.
  27. A. Ahmadzadeh, V. Jamali, and R. Schober, “Molecule harvesting transmitter model for molecular communication systems,” IEEE Open Journal of the Communications Society, vol. 3, pp. 391–410, 2022.
  28. B. D. Unluturk, A. O. Bicen, and I. F. Akyildiz, “Genetically engineered bacteria-based biotransceivers for molecular communication,” IEEE Transactions on Communications, vol. 63, no. 4, pp. 1271–1281, 2015.
  29. A. W. Eckford, B. Kuznets-Speck, M. Hinczewski, and P. J. Thomas, “Thermodynamic properties of molecular communication,” in 2018 IEEE International Symposium on Information Theory (ISIT).   IEEE, 2018, pp. 2545–2549.
  30. U. A. Chude-Okonkwo, R. Malekian, and B. T. Maharaj, “Diffusion-controlled interface kinetics-inclusive system-theoretic propagation models for molecular communication systems,” EURASIP Journal on Advances in Signal Processing, vol. 2015, pp. 1–23, 2015.
  31. X. Huang, Y. Fang, A. Noel, and N. Yang, “Membrane fusion-based transmitter design for molecular communication systems,” in 2021 IEEE International Conference on Communications (ICC).   IEEE, 2021, pp. 1–6.
  32. M. Rezaei, H. K. Rudsari, M. Javan, N. Mokari, E. A. Jorswieck, and M. Orooji, “Molecular communication transmitter design in limited-capacity storage regime,” IEEE Transactions on NanoBioscience, vol. 22, no. 2, pp. 212–222, 2023.
  33. M. Alarcón-Correa, D. Walker, T. Qiu, and P. Fischer, “Nanomotors,” The European Physical Journal Special Topics, vol. 225, pp. 2241–2254, 2016.
  34. F. Novotnỳ, H. Wang, and M. Pumera, “Nanorobots: machines squeezed between molecular motors and micromotors,” Chem, vol. 6, no. 4, pp. 867–884, 2020.
  35. R. Chattamvelli and R. Shanmugam, “Discrete distributions in engineering and the applied sciences,” Synthesis Lectures on Mathematics and Statistics, vol. 12, no. 2, pp. 1–227, 2020.
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