The arrival of molecules in molecular communication via diffusion (MCvD) is a counting process and exhibits binomial distribution by its nature. Even if the arrival of molecules is described well by the binomial process, the binomial cumulative distribution function (CDF) is difficult to work with when considering consecutively sent symbols. Therefore, in the literature, Poisson and Gaussian approximations of the binomial distribution are used. In this paper, we analyze these two approximations of the binomial model of the arrival process in MCvD with drift. We investigate the regions in which either Poisson or Gaussian model is better in terms of root mean squared error (RMSE) of the CDFs with varying the distance, drift velocity, and the number of emitted molecules. Moreover, we confirm the boundaries of the region via numerical simulations and derive the error probabilities for continuous communication and analyze which model approximates it more accurately.
|Title of host publication||Proceedings of the 2nd ACM International Conference on Nanoscale Computing and Communication, ACM NANOCOM 2015|
|Publisher||Association for Computing Machinery, Inc|
|Publication status||Published - 2015 Sep 21|
|Event||2nd ACM International Conference on Nanoscale Computing and Communication, ACM NANOCOM 2015 - Boston, United States|
Duration: 2015 Sep 21 → 2015 Sep 22
|Name||Proceedings of the 2nd ACM International Conference on Nanoscale Computing and Communication, ACM NANOCOM 2015|
|Other||2nd ACM International Conference on Nanoscale Computing and Communication, ACM NANOCOM 2015|
|Period||15/9/21 → 15/9/22|
Bibliographical noteFunding Information:
This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ?IT Consilience Creative Program? (IITP-2015-R0346-15-1008) supervised by the IITP (Institute for Information & Communications Technology Promotion) and by the Basic Science Research Program (2014R1A1A1002186) funded by the MSIP, Korea, through the National Research Foundation of Korea.
All Science Journal Classification (ASJC) codes
- Computational Theory and Mathematics
- Computer Networks and Communications