A molecular communication channel is determined by the received signal, which forms the basis for studies that are focusing on modulation, receiver design, capacity, and coding. Therefore, it is crucial to model the number of received molecules until time t. Received signal is modeled analytically when the transmitter is a point and the receiver is an absorbing sphere. Modeling the diffusion-based molecular communication channel with the first-hitting process (i.e., with an absorbing receiver) is an open issue when the transmitter is a reflecting spherical body. In this paper, we utilize the artificial neural networks technique to model the received signal for a spherical transmitter and a perfectly absorbing receiver (i.e., first-hitting process). The proposed technique may be utilized in other studies that assume a spherical transmitter instead of a point transmitter.
|Title of host publication||2017 IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2017|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||5|
|Publication status||Published - 2018 Jan 31|
|Event||2017 IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2017 - Istanbul, Turkey|
Duration: 2017 Jun 5 → 2017 Jun 8
|Name||2017 IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2017|
|Other||2017 IEEE International Black Sea Conference on Communications and Networking, BlackSeaCom 2017|
|Period||17/6/5 → 17/6/8|
Bibliographical noteFunding Information:
This research has been supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the “ICT Consilience Creative Program” (IITP-R0346-16-1008) 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
- Artificial Intelligence
- Computer Networks and Communications
- Signal Processing