多接收机自由扩散分子通信信道建模

doi:10.11959/j.issn.1000-436x.2021151

通信学报 ›› 2021, Vol. 42 ›› Issue (7): 107-116.doi: 10.11959/j.issn.1000-436x.2021151

多接收机自由扩散分子通信信道建模

孙卓, 鲍煦, 林颉, 张文策

江苏大学计算机科学与通信工程学院，江苏镇江 212013

修回日期:2021-03-05 出版日期:2021-07-25 发布日期:2021-07-01
作者简介:孙卓（1994− ），男，吉林镇赉人，江苏大学博士生，主要研究方向为分子通信
鲍煦（1982− ），男，江苏靖江人，博士，江苏大学教授、博士生导师，主要研究方向为分子通信、智慧无线通信、纳米传感网技术
林颉（1994− ），女，福建平潭人，江苏大学硕士生，主要研究方向为分子通信
张文策（1987− ），男，河北保定人，博士，江苏大学副教授、硕士生导师，主要研究方向为分子通信、大规模 MIMO、智能反射面技术
基金资助:
江苏省重点研发计划基金资助项目(BE2018108);国家自然科学基金资助项目(61772243);江苏省六大人才高峰高层次人才计划资助项目(XYDXX-115)

Channel modeling of molecular communication via free diffusion with multiple receiver

Zhuo SUN, Xu BAO, Jie LIN, Wence ZHANG

School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China

Revised:2021-03-05 Online:2021-07-25 Published:2021-07-01
Supported by:
The Key Research and Development Project of Jiangsu Province(BE2018108);The National Natural Science Foundation of China(61772243);Six Talent Peak High Level Talent Plan Projects of Jiangsu Province(XYDXX-115)

摘要/Abstract

摘要：

考虑点源、一对吸收机和透明机共存场景，在透明机接收分子概率模型基础上引入干扰因子，考虑空间中吸收机对该透明机接收分子的影响，建立吸收机干扰下点源-透明机信道模型，并结合人工神经网络使用Levenberg-Marquardt算法对信道模型参数进行学习和预测。仿真结果不仅验证了所提信道模型的有效性，还表明空间中任意点峰值时刻与点源到该点的距离平方成正比，与分子扩散系数成反比，峰值时刻不受空间中的吸收机影响。

关键词: 分子通信, 自由扩散, 多接收机, 信道建模

Abstract:

A coexistence scenario with a point source, a pair of absorbing and transparent receiver was considered, an interference factor was introduced in the proposed channel model based on the receiving molecular probability in the transparent receiver considering the influences of the absorbing receiver on the transparent one.Furthermore, the channel model of point source and transparent receiver had been proposed by using Levenberg-Marquardt algorithm combined with artificial neural network to study and predict channel model parameters.The simulation results not only verify the effectiveness of the proposed channel model, but also show that the peak time of any point in the environment is directly proportional to the square of the distance from the point source to the receiver, and inversely proportional to the molecular diffusion coefficient, and the peak time is not affected by the absorbing receiver in the environment.

Key words: molecular communication, free diffusion, multi receiver, channel model

中图分类号:

TN92

孙卓, 鲍煦, 林颉, 张文策. 多接收机自由扩散分子通信信道建模[J]. 通信学报, 2021, 42(7): 107-116.

Zhuo SUN, Xu BAO, Jie LIN, Wence ZHANG. Channel modeling of molecular communication via free diffusion with multiple receiver[J]. Journal on Communications, 2021, 42(7): 107-116.

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参考文献 28

[1]	DRESSLER F , FISCHER S . Connecting in-body nano communication with body area networks:challenges and opportunities of the Internet of Nano things[J]. Nano Communication Networks, 2015,6(2): 29-38.
[2]	AKYILDIZ I F , BRUNETTI F , BLáZQUEZ C , . Nanonetworks:a new communication paradigm[J]. Computer Networks, 2008,52(12): 2260-2279.
[3]	BUSH S F . Nanoscale communication networks[M]. Boston: Artech House Press, 2010.
[4]	GREGORI M , AKYILDIZ I F . A new nanonetwork architecture using flagellated bacteria and catalytic nanomotors[J]. IEEE Journal on Selected Areas in Communications, 2010,28(4): 612-619.
[5]	ZHOU Y Q , TIAN L , LIU L ,et al. Fog computing enabled future mobile communication networks:a convergence of communication and computing[J]. IEEE Communications Magazine, 2019,57(5): 20-27.
[6]	ZHOU Y Q , LIU L , WANG L ,et al. Service-aware 6G:an intelligent and open network based on the convergence of communication,com puting and caching[J]. Digital Communications and Networks, 2020,6(3): 253-260.
[7]	AKYILDIZ I F , JORNET J M . The Internet of nano-things[J]. IEEE Wireless Communications, 2010,17(6): 58-63.
[8]	NAKANO T , SUDA T , KOUJIN T ,et al. Molecular communication through gap junction channels:System design,experiments and modeling[C]// 2007 2nd Bio-Inspired Models of Network,Information and Computing Systems. Piscataway:IEEE Press, 2007: 139-146.
[9]	AKAN O B , RAMEZANI H , KHAN T ,et al. Fundamentals of molecular information and communication science[J]. Proceedings of the IEEE, 2017,105(2): 306-318.
[10]	FARSAD N , YILMAZ H B , ECKFORD A ,et al. A comprehensive survey of recent advancements in molecular communication[J]. IEEE Communications Surveys and Tutorials, 2016,18(3): 1887-1919.
[11]	PIEROBON M , AKYILDIZ I F . A physical end-to-end model for molecular communication in nanonetworks[J]. IEEE Journal on Selected Areas in Communications, 2010,28(4): 602-611.
[12]	JAMALI V , AHMADZADEH A , WICKE W ,et al. Channel modeling for diffusive molecular communication—a tutorial review[J]. Proceedings of the IEEE, 2019,107(7): 1256-1301.
[13]	BERG H C . Random walks in biology[M]. Princeton： Princeton University Press， 1993.
[14]	YILMAZ H B , HEREN A C , TUGCU T ,et al. Three-dimensional channel characteristics for molecular communications with an absorbing receiver[J]. IEEE Communications Letters, 2014,18(6): 929-932.
[15]	DENG Y S , NOEL A , ELKASHLAN M ,et al. Modeling and simulation of molecular communication systems with a reversible adsorption receiver[J]. IEEE Transactions on Molecular,Biological and Multi-Scale Communications, 2015,1(4): 347-362.
[16]	YILMAZ H B , SUK G Y , CHAE C B . Chemical propagation pattern for molecular communications[J]. IEEE Wireless Communications Letters, 2017,6(2): 226-229.
[17]	GENC G , KARA Y E , TUGCU T ,et al. Reception modeling of sphere-to-sphere molecular communication via diffusion[J]. Nano Communication Networks, 2018,16: 69-80.
[18]	BAO X , ZHU Y F , ZHANG W C . Channel characteristics for molecular communication via diffusion with a spherical boundary[J]. IEEE Wireless Communications Letters, 2019,8(3): 957-960.
[19]	HUANG S , LIN L , XU J ,et al. Molecular communication via subdiffusion with a spherical absorbing receiver[J]. IEEE Wireless Communications Letters, 2020,9(10): 1682-1686.
[20]	CAO T N , TRINH D P , JEONG Y ,et al. Anomalous diffusion in molecular communication[J]. IEEE Communications Letters, 2015,19(10): 1674-1677.
[21]	ARIFLER D , ARIFLER D . Monte Carlo analysis of molecule absorption probabilities in diffusion-based nanoscale communication systems with multiple receivers[J]. IEEE Transactions on NanoBioscience, 2017,16(3): 157-165.
[22]	DENG Y S , NOEL A , GUO W S ,et al. Analyzing large-scale multiuser molecular communication via 3-D stochastic geometry[J]. IEEE Transactions on Molecular,Biological and Multi-Scale Communications, 2017,3(2): 118-133.
[23]	ZABINI F . Spatially distributed molecular communications:an asynchronous stochastic model[J]. IEEE Communications Letters, 2018,22(7): 1326-1329.
[24]	BAO X , LIN J , ZHANG W C . Channel modeling of molecular communication via diffusion with multiple absorbing receivers[J]. IEEE Wireless Communications Letters, 2019,8(3): 809-812.
[25]	DINC F . Analytical estimation for the impulse response of an n-dimensional diffusion channel with an absorbing receiver[J]. Journal of Physics A:Mathematical and Theoretical, 2019,52(11): 11LT01.
[26]	HUANG X Y , FANG Y T , NOEL A ,et al. Channel characterization for 1-D molecular communication with two absorbing receivers[J]. IEEE Communications Letters, 2020,24(6): 1150-1154.
[27]	KOO B H , LEE C , YILMAZ H B ,et al. Molecular MIMO:from theory to prototype[J]. IEEE Journal on Selected Areas in Communications, 2016,34(3): 600-614.
[28]	LU Y , HIGGINS M D , NOEL A ,et al. The effect of two receivers on broadcast molecular communication systems[J]. IEEE Transactions on NanoBioscience, 2016,15(8): 891-900.

参数	取值
点源S发射的总分子数	20 000
扩散系数D/(μm²·s^-1)	100
吸收机R₁的半径r₁/μm	2
透明机R₂ 的体积V₂/μm³	1
仿真步长Δt /s	0.001
仿真总时长/s	2
吸收机的吸收概率P_react	1
仿真次数	111

d₂/μm	α	k₁	k₂	R-square	SSE	RMSE
3	60°	7.015 7	0.038 2	0.999 6	4.018 6×10^-6	6.403 7×10^-6
4	150°	2.868 8	0.023 8	0.999 9	2.781 1×10^-7	1.684 6×10^-6

训练算法	全称	特点
BFG	BFGS quasi-Newton algorithm	对于较小的网络是一种有效的训练算法，对于非常大的网络效率并不高
BR	Bayesian regularization	使用此函数训练的网络必须使用MSE或SSE性能函数
CGB	conjugate gradient with Powell-beale restart	据Powell-Beale重启的共轭梯度反向传播来更新权重和偏差值的网络训练函数
CGF	conjugate gradient backpropagation with Fletcher-Reeves update	共轭梯度法中存储量要求最小的算法，但泛化能力较差
CGP	conjugate gradient backpropagation with Polak-Ribiére updates	要求的存储量大，但收敛速度快
LM	Levenberg-Marquardt	避免了直接计算Hessian矩阵，从而减少了训练中的计算量，可以更快地完成计算，但是需要较大内存，而且对于大型矩阵收敛速度慢
OSS	one-step secant backpropagation	比 BFG 算法占用更少的存储空间和计算量。与共轭梯度算法相比，它每完成一次训练都需要更多的存储空间和计算量
RP	resilient backpropagation	可以在不降低网络设计准确性的前提下，提供更快的权重和偏差的局部自适应。运行时需要存储每个权重和偏差的更新值，会占用较多的存储空间
SCG	scaled conjugate gradient	将模值信赖域算法与共轭梯度算法结合起来，减少了用于调整方向时搜索网络的时间

训练算法	R^-square	SSE	RMSE
BFG	9.037 4×10^-1	4.102 4×10²	7.261 5×10^-1
BR	7.708 2×10^-1	3.804 8×10³	2.211 4
CGB	4.286 3×10^-1	9.486 1×10³	3.491 8
CGF	8.087 6×10^-1	2.152 6×10³	1.663 4
CGP	5.853 7×10^-1	3.729 8×10³	2.189 5
LM	9.759 9×10^-1	1.542 7×10³	1.408 2
OSS	6.886 6×10^-1	4.152 7×10³	2.310 3
RP	7.565 6×10^-1	3.729 3×10³	2.189 4
SCG	7.772 5×10^-1	2.310 1×10³	1.723 2

多接收机自由扩散分子通信信道建模

Channel modeling of molecular communication via free diffusion with multiple receiver

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