4.8 Article

Resource Allocation for Multiuser Molecular Communication Systems Oriented to the Internet of Medical Things

期刊

IEEE INTERNET OF THINGS JOURNAL
卷 8, 期 21, 页码 15939-15952

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2021.3051391

关键词

Resource management; Optimization; Transmitters; Nanobioscience; Internet of Things; Receivers; COVID-19; Combinatorial optimization; molecular communication (MC); molecular resource allocation; multiple access; sum rate; user fairness

资金

  1. National Natural Science Foundation of China [61871190]
  2. Natural Science Foundation of Guangdong Province [2018B030306005]
  3. Pearl River Nova Program of Guangzhou [201806010171]
  4. Fundamental Research Funds for the Central Universities [2019SJ02]
  5. National Research Foundation of Korea [NRF2020R1A2C4001941]

向作者/读者索取更多资源

The article discusses the optimization issues of multi-user molecular communication systems in the Internet of Bio-Nano Things, proposing a novel multiuser MC system based on molecular division multiple access technology. The study focuses on user fairness, introducing two types of molecule allocation strategies, and analyzing two-user and three-user scenarios to show that the new combination strategy outperforms benchmarks in terms of performance.
Communication between nanomachines 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 nanomachine clusters, it is imperative to study multiple-access MC. In this article, based on the molecular division multiple access technology, we propose a novel multiuser 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. In 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.

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