Deep Learning-Based Estimation of Emission Time and Arrival Time in Diffusive Multi-Receiver Molecular Communication

IF 2.3 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Transactions on Molecular, Biological, and Multi-Scale Communications Pub Date : 2025-02-27 DOI:10.1109/TMBMC.2025.3546503

Zhen Cheng;Heng Liu;Ziyan Xu;Jiaxin Li;Kaikai Chi

引用次数: 0

Abstract

Diffusive molecular communication (DMC) utilizes the emission, diffusion and reception of molecules to transmit information. It has promising prospects in the field of drug delivery. The estimation of emission time and arrival time of molecules in DMC system plays important roles in the resource consumption at the receivers. Existing traditional strategies for the derivation of emission time and arrival time mainly focus on known channel state information (CSI). In this paper, we propose a deep learning method for estimating emission time and arrival time of the molecules in DMC system with unknown CSI by using Transformer-based model, respectively. The simulation results show that the emission time and arrival time of molecules can be accurately estimated by the Transformer-based model which exhibits better estimation and generalization abilities than deep neural network (DNN) model.

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基于深度学习的扩散多接收机分子通信发射时间和到达时间估计

扩散分子通信（DMC）利用分子的发射、扩散和接收来传递信息。在给药领域具有广阔的应用前景。DMC系统中分子发射时间和到达时间的估计对接收机的资源消耗起着重要的作用。现有的传统发射时间和到达时间的推导策略主要集中在已知信道状态信息上。在本文中，我们提出了一种深度学习方法，分别利用基于变压器的模型估计未知CSI的DMC系统中分子的发射时间和到达时间。仿真结果表明，基于变压器的模型能够准确估计分子的发射时间和到达时间，具有比深度神经网络（DNN）模型更好的估计能力和泛化能力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Molecular, Biological, and Multi-Scale Communications Mathematics-Modeling and Simulation

CiteScore

3.90

自引率

13.60%

发文量

期刊介绍： As a result of recent advances in MEMS/NEMS and systems biology, as well as the emergence of synthetic bacteria and lab/process-on-a-chip techniques, it is now possible to design chemical “circuits”, custom organisms, micro/nanoscale swarms of devices, and a host of other new systems. This success opens up a new frontier for interdisciplinary communications techniques using chemistry, biology, and other principles that have not been considered in the communications literature. The IEEE Transactions on Molecular, Biological, and Multi-Scale Communications (T-MBMSC) is devoted to the principles, design, and analysis of communication systems that use physics beyond classical electromagnetism. This includes molecular, quantum, and other physical, chemical and biological techniques; as well as new communication techniques at small scales or across multiple scales (e.g., nano to micro to macro; note that strictly nanoscale systems, 1-100 nm, are outside the scope of this journal). Original research articles on one or more of the following topics are within scope: mathematical modeling, information/communication and network theoretic analysis, standardization and industrial applications, and analytical or experimental studies on communication processes or networks in biology. Contributions on related topics may also be considered for publication. Contributions from researchers outside the IEEE’s typical audience are encouraged.