Abstract
Molecular communication (MC) is considered to be a promising technology to realize the Internet of Nano Things (IoNT), especially the biomedical IoNT. In the construction of IoNT, communication between nano-machines is still an important topic, where multiple-access MC is imperative to be studied due to the multiple nano-machine clusters in IoNT. In this paper, a novel multi-user MC system based on the molecular division multiple access technology is proposed, where information molecules with different diffusion coefficients are first employed. Moreover, we employ the max-min rate fairness as a criterion to investigate the optimization of molecular resource allocation, including the assignment for types of molecules and the number of associated molecules. Two assignment strategies for types of molecules, i.e., best-to-best (BTB) and best-to-worst (BTW), are proposed. Subsequently, we analytically deduce the optimal allocation for the number of molecules when types of molecules are fixed for all users. Finally, numerical results show that the combination of BTW and the optimal allocation for the number of molecules exhibits the best performance.
| Original language | English |
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| Title of host publication | ICC 2021 - IEEE International Conference on Communications, Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781728171227 |
| DOIs | |
| Publication status | Published - 2021 Jun |
| Event | 2021 IEEE International Conference on Communications, ICC 2021 - Virtual, Online, Canada Duration: 2021 Jun 14 → 2021 Jun 23 |
Publication series
| Name | IEEE International Conference on Communications |
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| ISSN (Print) | 1550-3607 |
Conference
| Conference | 2021 IEEE International Conference on Communications, ICC 2021 |
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| Country/Territory | Canada |
| City | Virtual, Online |
| Period | 21/6/14 → 21/6/23 |
Bibliographical note
Funding Information:ACKNOWLEDGEMENTS The work was supported in part by the National Natural Science Foundation of China under Grant 61871190, in part by the Natural Science Foundation of Guangdong Province under Grant 2018B030306005, in part by the Pearl River Nova Program of Guangzhou under Grant 201806010171, in part by the Fundamental Research Funds for the Central Universities under Grant 2019SJ02, in part by the Key Program of Marine Economy Development(Six Marine Industries) Special Foundation of Department of Natural Resources of Guangdong Province(GDNRC [2020]009), and in part by the National Research Foundation of Korea (NRF-2020R1A2C4001941).
Publisher Copyright:
© 2021 IEEE.
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Electrical and Electronic Engineering