Resource Allocation for Multi-User Molecular Communication Systems Oriented to The Internet of Medical Things

Xuan Chen, Miaowen Wen, Chan Byoung Chae, Lie Liang Yang, Fei Ji, Kostromitin Konstantin Igorevich

Research output: Contribution to journalArticlepeer-review

Abstract

Communication between nano-machines is still an important topic in the construction of the Internet of Bio-Nano Things (IoBNT). Currently, molecular communication (MC) is expected to be a promising technology to realize IoBNT. To effectively serve the IoBNT composed of multiple nano-machine clusters, it is imperative to study multiple-access MC. In this paper, based on the molecular division multiple access technology, we propose a novel multi-user MC system, where information molecules with different diffusion coefficients are first employed. Aiming at the user fairness in the considered system, we investigate the optimization of molecular resource allocation, including the assignment of the types of molecules and the number of molecules of a type. Specifically, three performance metrics are considered, namely, min-max fairness for error probability, max-min fairness for achievable rate, and weighted sum rate maximization. Moreover, we propose two assignment strategies for types of molecules, i.e., best-to-best (BTB) and best-to-worst (BTW). Subsequently, for a two-user scenario, we analytically derive the optimal allocation for the number of molecules when types of molecules are fixed for all users. By contrast, for a three-user scenario, we prove that the BTB and BTW schemes with the optimal allocation for the number of molecules can provide the lower and upper bounds on system performance, respectively. Finally, numerical results show that the combination of BTW and the optimal allocation for the number of molecules yields better performance than the benchmarks.

Original languageEnglish
JournalIEEE Internet of Things Journal
DOIs
Publication statusAccepted/In press - 2021

Bibliographical note

Publisher Copyright:
IEEE

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

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