On Channel Capacity and Error Compensation in Molecular Communication

  • Baris Atakan
  • Ozgur B. Akan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5410)


Molecular communication is a novel paradigm that uses molecules as an information carrier to enable nanomachines to communicate with each other. Controlled molecule delivery between two nanomachines is one of the most important challenges which must be addressed to enable the molecular communication. Therefore, it is essential to develop an information theoretical approach to find out communication capacity of the molecular channel. In this paper, we develop an information theoretical approach for capacity of a molecular channel between two nanomachines. Using the principles of mass action kinetics, we first introduce a molecule delivery model for the molecular communication between two nanomachines called as Transmitter Nanomachine (TN) and Receiver Nanomachine (RN). Then, we derive a closed form expression for capacity of the channel between TN and RN. Furthermore, we propose an adaptive Molecular Error Compensation (MEC) scheme for the molecular communication between TN and RN. MEC allows TN to select an appropriate molecular bit transmission probability to maximize molecular communication capacity with respect to environmental factors such as temperature and distance between nanomachines. Numerical analysis show that selecting appropriate molecular communication parameters such as concentration of emitted molecules, duration of molecule emission, and molecular bit transmission probability it can be possible to achieve high molecular communication capacity for the molecular communication channel between two nanomachines. Moreover, the numerical analysis reveals that MEC provides more than % 100 capacity improvement in the molecular communication selecting the most appropriate molecular transmission probability.


Molecular communication nanomachines molecular bit information theory channel capacity error compensation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Hiyama, S., Moritani, Y., Suda, T., Egashira, R., Enomoto, A., Moore, M., Nakano, T.: Molecular Communication. In: NSTI Nanotech, Anaheim, California, USA, pp. 391–394 (2005)Google Scholar
  2. 2.
    Whitesides, G.M.: The Once and Future Nanomachine. Scientific American 285(3), 78–83 (2001)CrossRefGoogle Scholar
  3. 3.
    Suda, T., Moore, M., Nakano, T., Egashira, R., Enomoto, A.: Exploratory Research on Molecular Communication between Nanomachines. In: Genetic and Evolutionary Computation Conference (GECCO), Washington, DC, USA (2005)Google Scholar
  4. 4.
    Moore, M., Enomoto, A., Nakano, T., Egashira, R., Suda, T., Kayasuga, A., Kojima, H., Sakakibara, H., Oiwa, K.: A Design of a Molecular Communication System for Nanomachines Using Molecular Motors. In: IEEE PERCOMW, Italy, pp. 554–559 (2006)Google Scholar
  5. 5.
    Moritani, Y., Hiyama, S., Suda, T.: Molecular Communication for Health Care Applications. In: IEEE PERCOMW 2006, Italy, pp. 549–553 (2006)Google Scholar
  6. 6.
    Nakano, T., Suda, T., Moore, M., Egashira, R., Enomoto, A., Arima, K.: Molecular Communication for Nanomachines Using Intercellular Calcium Signaling. In: IEEE Conference on Nanotechnology, Nagoya, Japan, pp. 478–481 (2005)Google Scholar
  7. 7.
    Hiyama, S., Isogawa, Y., Suda, T., Moritani, Y., Sutoh, K.: A Design of an Autonomous Molecule Loading/Transporting/Unloading System Using DNA Hybridization and Biomolecular Linear Motors. In: European Nano Systems, Paris, France, pp. 75–80 (2005)Google Scholar
  8. 8.
    Atakan, B., Akan, O.B.: An Information Theoretical Approach for Molecular Communication. In: ACM BIONETICS 2007, Budapest, Hungary (2007)Google Scholar
  9. 9.
    Rospars, J.P., Krivan, V., Lansky, P.: Perireceptor and receptor events in olfaction. Comparison of concentration and flux detectors: a modeling study. Chem. Sens. 25, 293–311 (2000)Google Scholar
  10. 10.
    Krivan, V., Lansky, P., Rospars, J.P.: Coding of periodic pulse stimulation in chemoreceptors. Elsevier Biosystem 67, 121–128 (2002)Google Scholar
  11. 11.
    Saxton, M.J.: Anomalous Diffusion Due to Binding: A Monte Carlo Study. Biophysical Journal 70, 1250–1262 (1996)CrossRefGoogle Scholar
  12. 12.
    Long, M., Lü, S., Sun, G.: Kinetics of Receptor-Ligand Interactions in Immune Responses. Cell. & Mol. Immuno. 3(2), 79–86 (2006)Google Scholar
  13. 13.
    Bell, G.I.: Models for the specific adhesion of cells to cells. Sciences 200, 618–627 (1978)Google Scholar
  14. 14.
    Camacho, C.J., Kimura, S.R., DeLisi, C., Vajda, S.: Kinetics of Desolvation-Mediated Protein Binding. Biophysical Journal 78, 1094–1105 (2000)CrossRefGoogle Scholar
  15. 15.
    Cover, T.M., Thomas, J.A.: Elements of information theory. John Wiley-Sons, Chichester (2006)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Baris Atakan
    • 1
  • Ozgur B. Akan
    • 1
  1. 1.Next generation Wireless Communications Laboratory Department of Electrical and Electronics EngineeringMiddle East Technical UniversityAnkaraTurkey

Personalised recommendations