3D Stochastic Geometry Model for Large-Scale Molecular Communication Systems

3D Stochastic Geometry Model for Large-Scale Molecular Communication Systems
复制标题

大规模分子通信系统的 3D 随机几何模型

DOI:
10.1109/glocom.2016.7841486
复制
发表时间:
2016
期刊:
2016 IEEE Global Communications Conference (GLOBECOM)
影响因子:
--
通讯作者:
M. Elkashlan
M. Elkashlan
中科院分区:
--
文献类型:
--
作者:
Yansha Deng;Adam Noel;Weisi Guo;A. Nallanathan;M. Elkashlan

文献摘要

参考文献

被引文献

相似文献

利用化学分子传递信息是生物学在多距离尺度上不可分割的一部分,近年来引起了生物工程和通信领域的兴趣。由于大量发射器处于随机距离(例如,由于移动性),接收器处的集体信号强度(即接收器内观察到的分子的预期数量)会对分子通信系统的可靠性和效率产生重大影响。对来自多个扩散源的集体信号进行建模可能在计算和分析上具有挑战性。在本文中,我们提出了由随机放置的发射机引起的集体信号强度的第一个可处理的分析模型,其位置被建模为三维(3D)空间中的齐次泊松点过程。通过应用随机几何,我们推导了在完全吸收接收器和被动接收器上观察到的分子的期望数的解析表达式。我们的研究结果表明,两种类型的接收器的集体信号强度随发射机密度的增加而成比例地增加。所提出的框架极大地简化了通信和生物应用中大规模分子系统的分析。
Information delivery using chemical molecules is an integral part of biology at multiple distance scales and has attracted recent interest in bioengineering and communication. The collective signal strength at the receiver (i.e., the expected number of observed molecules inside the receiver), resulting from a large number of transmitters at random distances (e.g., due to mobility), can have a major impact on the reliability and efficiency of the molecular communication system. Modeling the collective signal from multiple diffusion sources can be computationally and analytically challenging. In this paper, we present the first tractable analytical model for the collective signal strength due to randomly-placed transmitters, whose positions are modelled as a homogeneous Poisson point process in three-dimensional (3D) space. By applying stochastic geometry, we derive analytical expressions for the expected number of observed molecules at a fully absorbing receiver and a passive receiver. Our results reveal that the collective signal strength at both types of receivers increases proportionally with increasing transmitter density. The proposed framework dramatically simplifies the analysis of large-scale molecular systems in both communication and biological applications.
DOI: 10.1109/tifs.2016.2516917
发表时间: 2016-06-01
影响因子: 6.8
作者:
Deng, Yansha;Wang, Lifeng;Mallik, Ranjan K.
通讯作者: Mallik, Ranjan K.