Information Theory of Molecular Communication: Directions and Challenges

被引:43
作者
Gohari A. [1 ]
Mirmohseni M. [1 ]
Nasiri-Kenari M. [1 ]
机构
[1] Department of Electrical Engineering, Sharif University of Technology, Tehran
来源
| 2016年 / Institute of Electrical and Electronics Engineers Inc., United States卷 / 02期
关键词
Brownian motion; Channel capacity; Information theory; Molecular communication;
D O I
10.1109/TMBMC.2016.2640284
中图分类号
学科分类号
摘要
Molecular communication (MC) is a communication strategy that uses molecules as carriers of information, and is widely used by biological cells. As an interdisciplinary topic, it has been studied by biologists, communication theorists and a growing number of information theorists. This paper aims to specifically bring MC to the attention of information theorists. To do this, we first highlight the unique mathematical challenges of studying the capacity of molecular channels. Addressing these problems requires use of known, or development of new mathematical tools. Toward this goal, we review a subjective selection of the existing literature on information theoretic aspect of MC The emphasis here is on the mathematical techniques used, rather than on the setup or modeling of a specific paper. Finally, as an example, we propose a concrete information theoretic problem that was motivated by our study of MC. © 2017 IEEE.
引用
收藏
页码:120 / 142
页数:22
相关论文
共 101 条
  • [1] Pierobon M., Akyildiz I.F., A physical end-to-end model for molecular communication in nanonetworks, IEEE J. Sel. Areas Commun., 28, 4, pp. 602-611, (2010)
  • [2] Nakano T., Moore M.J., Wei F., Vasilakos A.V., Shuai J., Molecular communication and networking: Opportunities and challenges, IEEE Trans. Nanobiosci., 11, 2, pp. 135-148, (2012)
  • [3] Farsad N., Yilmaz H.B., Eckford A., Chae C.-B., Guo W., A comprehensive survey of recent advancements in molecular communication, IEEE Commun. Surveys Tuts., 18, 3, pp. 1887-1919, (2016)
  • [4] Gastpar M., Rimoldi B., Vetterli M., To code, or not to code: Lossy source-channel communication revisited, IEEE Trans. Inf. Theory, 49, 5, pp. 1147-1158, (2003)
  • [5] Mosayebi R., Arjmandi H., Gohari A., Nasiri-Kenari M., Mitra U., Receivers for diffusion-based molecular communication: Exploiting memory and sampling rate, IEEE J. Sel. Areas Commun., 32, 12, pp. 2368-2380, (2014)
  • [6] Movahednasab M., Soleimanifar M., Gohari A., Nasiri-Kenari M., Mitra U., Adaptive transmission rate with a fixed threshold decoder for diffusion-based molecular communication, IEEE Trans. Commun., 64, 1, pp. 236-248, (2016)
  • [7] Yao A.C., Theory and application of trapdoor functions, Proc. 23rd Annu. IEEE Symp. Found. Comput. Sci., pp. 80-91, (1982)
  • [8] Hastad J., Impagliazzo R., Levin L.A., Luby M., A pseudorandom generator from any one-way function, SIAM J. Comput., 28, 4, pp. 1364-1396, (1999)
  • [9] El Gamal A., Greene J., Pang K., VLSI complexity of coding, Proc. MIT Conf. Adv. Res. VLSI, pp. 150-158, (1984)
  • [10] Grover P., Goldsmith A., Sahai A., Fundamental limits on the power consumption of encoding and decoding, Proc. IEEE Int. Symp. Inf. Theory (ISIT), pp. 2716-2720, (2012)