Abstract
In this paper, we propose adding enzymes to the propagation environment of a diffusive molecular communication system as a strategy for mitigating intersymbol interference. The enzymes form reaction intermediates with information molecules and then degrade them so that they have a smaller chance of interfering with future transmissions. We present the reaction-diffusion dynamics of this proposed system and derive a lower bound expression for the expected number of molecules observed at the receiver. We justify a particle-based simulation framework, and present simulation results that show both the accuracy of our expression and the potential for enzymes to improve communication performance.
The first author was supported by the Natural Sciences and Engineering Research Council of Canada, and a Walter C. Sumner Memorial Fellowship. Computing resources were provided by WestGrid and Compute/Calcul Canada.
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References
Alberts, B., Bray, D., Hopkin, K., Johnson, A., Lewis, J., Raff, M., Roberts, K., Walter, P.: Essential Cell Biology, 3rd edn. Garland Science, New York (2010)
Akyildiz, I.F., Brunetti, F., Blazquez, C.: Nanonetworks: a new communication paradigm. Comput. Netw. 52(12), 2260–2279 (2008)
Nakano, T., Moore, M.J., Wei, F., Vasilakos, A.V., Shuai, J.: Molecular communication and networking: opportunities and challenges. IEEE Trans. Nanobiosci. 11(2), 135–148 (2012)
Nelson, P.: Biological Physics: Energy, Information, Life, 1st edn. W. H. Freeman and Company, New York (2008)
Hiyama, S., Moritani, Y.: Molecular communication: harnessing biochemical materials to engineer biomimetic communication systems. Nano Commun. Netw. 1(1), 20–30 (2010)
Atakan, B., Akan, O.B.: Deterministic capacity of information flow in molecular nanonetworks. Nano Commun. Netw. 1(1), 31–42 (2010)
Mahfuz, M.U., Makrakis, D., Mouftah, H.T.: Characterization of intersymbol interference in concentration-encoded unicast molecular communication. In: Proceedings of 2011 IEEE CCECE, pp. 164–168, May 2011
Einolghozati, A., Sardari, M., Beirami, A., Fekri, F.: Capacity of discrete molecular diffusion channels. In: Proceedings of 2011 IEEE ISIT, pp. 723–727, August 2011
Chou, C.T.: Molecular circuits for decoding frequency coded signals in nano-communication networks. Nano Comm. Netw. 3(1), 46–56 (2012)
Nakano, T., Okaie, Y., Vasilakos, A.V.: Throughput and efficiency of molecular communication between nanomachines. In: Proceedings of 2012 IEEE WCNC, pp. 704–708, April 2012
Miorandi, D.: A stochastic model for molecular communications. Nano Commun. Netw. 2(4), 205–212 (2011)
Moore, M.J., Suda, T., Oiwa, K.: Molecular communication: modeling noise effects on information rate. IEEE Trans. Nanobiosci. 8(2), 169–180 (2009)
Naka, T., Shiba, K., Sakamoto, N.: A two-dimensional compartment model for the reaction-diffusion system of acetylcholine in the synaptic cleft at the neuromuscular junction. Biosystems 41(1), 17–27 (1997)
Cheng, Y., Suen, J.K., Radi, Z., Bond, S.D., Holst, M.J., McCammon, J.A.: Continuum simulations of acetylcholine diffusion with reaction-determined boundaries in neuromuscular junction models. Biophys. Chem. 127(3), 129–139 (2007)
Chang, R.: Physical Chemistry for the Biosciences. University Science Books, Sausalito (2005)
Gillespie, D.T.: A rigorous derivation of the chemical master equation. Phys. A 188(13), 404–425 (1992)
Pierobon, M., Akyildiz, I.F.: Information capacity of diffusion-based molecular communication in nanonetworks. In: Proceedings of 2011 IEEE INFOCOM 2011, pp. 506–510, April 2011
Pierobon, M., Akyildiz, I.F.: A physical end-to-end model for molecular communication in nanonetworks. IEEE J. Sel. Areas Commun. 28(4), 602–611 (2010)
Debnath, L.: Nonlinear Partial Differential Equations for Scientists and Engineers, 2nd edn. Birkhaeuser, Boston (2005)
Gillespie, D.T.: Stochastic simulation of chemical kinetics. Annu. Rev. Phys. Chem. 58(1), 35–55 (2007)
Iyengar, K.A., Harris, L.A., Clancy, P.: Accurate implementation of leaping in space: the spatial partitioned-leaping algorithm. J. Chem. Phys. 132(9), 094101 (2010)
Andrews, S.S., Bray, D.: Stochastic simulation of chemical reactions with spatial resolution and single molecule detail. Phys. Biol. 1(3), 137 (2004)
Bernstein, D.: Simulating mesoscopic reaction-diffusion systems using the Gillespie algorithm. Phys. Rev. E 71(4), 041103 (2005)
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© 2014 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Noel, A., Cheung, K., Schober, R. (2014). Improving Diffusion-Based Molecular Communication with Unanchored Enzymes. In: Di Caro, G., Theraulaz, G. (eds) Bio-Inspired Models of Network, Information, and Computing Systems. BIONETICS 2012. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 134. Springer, Cham. https://doi.org/10.1007/978-3-319-06944-9_13
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