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Performance Analysis and ISI Mitigation with Imperfect Transmitter in Molecular Communication (2404.02383v1)

Published 3 Apr 2024 in cs.IT and math.IT

Abstract: In molecular communication (MC), molecules are released from the transmitter to convey information. This paper considers a realistic molecule shift keying (MoSK) scenario with two species of molecule in two reservoirs, where the molecules are harvested from the environment and placed into different reservoirs, which are purified by exchanging molecules between the reservoirs. This process consumes energy, and for a reasonable energy cost, the reservoirs cannot be pure; thus, our MoSK transmitter is imperfect, releasing mixtures of both molecules for every symbol, resulting in inter-symbol interference (ISI). To mitigate ISI, the properties of the receiver are analyzed and a detection method based on the ratio of different molecules is proposed. Theoretical and simulation results are provided, showing that with the increase of energy cost, the system achieves better performance. The good performance of the proposed detection scheme is also demonstrated.

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References (43)
  1. 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.
  2. V. Jamali, A. Ahmadzadeh, W. Wicke, A. Noel, and R. Schober, “Channel modeling for diffusive molecular communication—a tutorial review,” Proceedings of the IEEE, vol. 107, no. 7, pp. 1256–1301, 2019.
  3. N.-R. Kim, A. W. Eckford, and C.-B. Chae, “Symbol interval optimization for molecular communication with drift,” IEEE transactions on Nanobioscience, vol. 13, no. 3, pp. 223–229, 2014.
  4. X. Bao, Q. Shen, Y. Zhu, and W. Zhang, “Relative localization for silent absorbing target in diffusive molecular communication system,” IEEE Internet of Things Journal, vol. 9, no. 7, pp. 5009–5018, 2021.
  5. M. Khalid, O. Amin, S. Ahmed, B. Shihada, and M.-S. Alouini, “Modeling of viral aerosol transmission and detection,” IEEE Transactions on Communications, vol. 68, no. 8, pp. 4859–4873, 2020.
  6. M. Schurwanz, P. A. Hoeher, S. Bhattacharjee, M. Damrath, L. Stratmann, and F. Dressler, “Infectious disease transmission via aerosol propagation from a molecular communication perspective: Shannon meets coronavirus,” IEEE Communications Magazine, vol. 59, no. 5, pp. 40–46, 2021.
  7. X. Chen, M. Wen, F. Ji, Y. Huang, Y. Tang, and A. W. Eckford, “Detection interval of aerosol propagation from the perspective of molecular communication: How long is enough?” IEEE Journal on Selected Areas in Communications, 2022.
  8. M. Ş. Kuran, H. B. Yilmaz, T. Tugcu, and B. Özerman, “Energy model for communication via diffusion in nanonetworks,” Nano Communication Networks, vol. 1, no. 2, pp. 86–95, 2010.
  9. M. Pierobon and I. F. Akyildiz, “Capacity of a diffusion-based molecular communication system with channel memory and molecular noise,” IEEE Transactions on Information Theory, vol. 59, no. 2, pp. 942–954, 2012.
  10. 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.
  11. B. Tepekule, A. E. Pusane, H. B. Yilmaz, C.-B. Chae, and T. Tugcu, “Isi mitigation techniques in molecular communication,” IEEE Transactions on Molecular, Biological and Multi-Scale Communications, vol. 1, no. 2, pp. 202–216, 2015.
  12. V. Musa, G. Piro, L. A. Grieco, and G. Boggia, “A lean control theoretic approach to energy-harvesting in diffusion-based molecular communications,” IEEE Communications Letters, vol. 24, no. 5, pp. 981–985, 2020.
  13. 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.
  14. B. A. Bilgin and O. B. Akan, “A fast algorithm for analysis of molecular communication in artificial synapse,” IEEE transactions on Nanobioscience, vol. 16, no. 6, pp. 408–417, 2017.
  15. Z. Cheng, Y. Tu, M. Xia, and K. Chi, “Energy efficiency analysis of multi-hop mobile diffusive molecular communication,” Nano Communication Networks, vol. 26, p. 100313, 2020.
  16. 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.
  17. R. Nordström and M. Malmsten, “Delivery systems for antimicrobial peptides,” Advances in colloid and interface science, vol. 242, pp. 17–34, 2017.
  18. M. C. Teixeira, C. Carbone, M. C. Sousa, M. Espina, M. L. Garcia, E. Sanchez-Lopez, and E. B. Souto, “Nanomedicines for the delivery of antimicrobial peptides (amps),” Nanomaterials, vol. 10, no. 3, p. 560, 2020.
  19. J. Li, S. Hu, W. Jian, C. Xie, and X. Yang, “Plant antimicrobial peptides: structures, functions, and applications,” Botanical Studies, vol. 62, no. 1, pp. 1–15, 2021.
  20. M. H. Kabir, S. R. Islam, and K. S. Kwak, “D-mosk modulation in molecular communications,” IEEE transactions on Nanobioscience, vol. 14, no. 6, pp. 680–683, 2015.
  21. L. Shi and L.-L. Yang, “Performance of diffusive molecular communication systems with binary molecular shift keying modulation.” IET Communications, vol. 14, no. 2, pp. 262–273, 2020.
  22. M. Wen, F. Liang, and Y. Tang, “Layered molecular shift keying for molecular communication via diffusion,” IEEE Communications Letters, 2021.
  23. H. Arjmandi, M. Movahednasab, A. Gohari, M. Mirmohseni, M. Nasiri-Kenari, and F. Fekri, “Isi-avoiding modulation for diffusion-based molecular communication,” IEEE Transactions on Molecular, Biological and Multi-Scale Communications, vol. 3, no. 1, pp. 48–59, 2017.
  24. A. O. Kislal, H. B. Yilmaz, A. E. Pusane, and T. Tugcu, “Isi-aware channel code design for molecular communication via diffusion,” IEEE transactions on Nanobioscience, vol. 18, no. 2, pp. 205–213, 2019.
  25. A. Keshavarz-Haddad, A. Jamshidi, and P. Akhkandi, “Inter-symbol interference reduction channel codes based on time gap in diffusion-based molecular communications,” Nano Communication Networks, vol. 19, pp. 148–156, 2019.
  26. Y. Tang, M. Wen, X. Chen, Y. Huang, and L.-L. Yang, “Molecular type permutation shift keying for molecular communication,” IEEE Transactions on Molecular, Biological and Multi-Scale Communications, vol. 6, no. 2, pp. 160–164, 2020.
  27. M. C. Gursoy, D. Seo, and U. Mitra, “A concentration-time hybrid modulation scheme for molecular communications,” IEEE Transactions on Molecular, Biological and Multi-Scale Communications, vol. 7, no. 4, pp. 288–299, 2021.
  28. B. Li, M. Sun, S. Wang, W. Guo, and C. Zhao, “Local convexity inspired low-complexity noncoherent signal detector for nanoscale molecular communications,” IEEE Transactions on Communications, vol. 64, no. 5, pp. 2079–2091, 2016.
  29. G. Chang, L. Lin, and H. Yan, “Adaptive detection and isi mitigation for mobile molecular communication,” IEEE Transactions on Nanobioscience, vol. 17, no. 1, pp. 21–35, 2017.
  30. A. Noel, K. C. Cheung, and R. Schober, “Optimal receiver design for diffusive molecular communication with flow and additive noise,” IEEE transactions on Nanobioscience, vol. 13, no. 3, pp. 350–362, 2014.
  31. A. Singhal, R. K. Mallik, and B. Lall, “Performance analysis of amplitude modulation schemes for diffusion-based molecular communication,” IEEE Transactions on Wireless Communications, vol. 14, no. 10, pp. 5681–5691, 2015.
  32. L. Brand, M. Garkisch, S. Lotter, M. Schäfer, A. Burkovski, H. Sticht, K. Castiglione, and R. Schober, “Media modulation based molecular communication,” IEEE Transactions on Communications, vol. 70, no. 11, pp. 7207–7223, 2022.
  33. S. Ghavami and F. Lahouti, “Abnormality detection in correlated gaussian molecular nano-networks: Design and analysis,” IEEE transactions on Nanobioscience, vol. 16, no. 3, pp. 189–202, 2017.
  34. 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.
  35. X. Qian, M. Di Renzo, and A. Eckford, “K-means clustering-aided non-coherent detection for molecular communications,” IEEE Transactions on Communications, vol. 69, no. 8, pp. 5456–5470, 2021.
  36. 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.
  37. X. Qian and M. Di Renzo, “Receiver design in molecular communications: An approach based on artificial neural networks,” in 2018 15th international symposium on wireless communication systems (ISWCS).   IEEE, 2018, pp. 1–5.
  38. X. Qian, M. Di Renzo, and A. Eckford, “Molecular communications: Model-based and data-driven receiver design and optimization,” IEEE Access, vol. 7, pp. 53 555–53 565, 2019.
  39. X. Huang, Y. Fang, A. Noel, and N. Yang, “Membrane fusion-based transmitter design for molecular communication systems,” in ICC 2021-IEEE International Conference on Communications.   IEEE, 2021, pp. 1–6.
  40. N.-R. Kim and C.-B. Chae, “Novel modulation techniques using isomers as messenger molecules for nano communication networks via diffusion,” IEEE Journal on Selected Areas in Communications, vol. 31, no. 12, pp. 847–856, 2013.
  41. D. Jing, Y. Li, and A. W. Eckford, “An extended kalman filter for distance estimation and power control in mobile molecular communication,” IEEE Transactions on Communications, 2022.
  42. N. Varshney, W. Haselmayr, and W. Guo, “On flow-induced diffusive mobile molecular communication: First hitting time and performance analysis,” IEEE Transactions on Molecular, Biological and Multi-Scale Communications, vol. 4, no. 4, pp. 195–207, 2018.
  43. Z. Luo, L. Lin, W. Guo, S. Wang, F. Liu, and H. Yan, “One symbol blind synchronization in simo molecular communication systems,” IEEE Wireless Communications Letters, vol. 7, no. 4, pp. 530–533, 2018.

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