Paper Info
Title
Initial Distance Estimation for Diffusive Mobile Molecular Communication Systems
Abstract
Mobile molecular communication (MC) attracts much attention in recent years where mobile nanomachines exchange information using molecules. In this paper, we consider a diffusion-based mobile MC system consisting a pair of diffusive nanomachines. Due to the Brownian motion of nanomachines, the distance between them is a stochastic process. In this paper, its probability density function (PDF) is derived by characterizing nanomachines' motion as Wiener process. Besides, the initial distance between nanomachines is a significant parameter of diffusive mobile MC systems. With the knowledge of initial distance, the expected channel impulse response (CIR) can be obtained and the detection threshold can be set in advance. A novel two-step scheme is proposed to estimate the initial distance by maximum likelihood (ML) estimation. Firstly, the releasing distance is estimated based on observations of the number of received molecules. Secondly, the estimation of the releasing distance is used as an observation to estimate the initial distance by ML estimation. The performance of proposed scheme is evaluated via particle-based simulation of the Brownian motion.
Year
DOI
Venue
2019
10.1109/ICCChinaW.2019.8849967
2019 IEEE/CIC International Conference on Communications Workshops in China (ICCC Workshops)
Keywords
Field
DocType
Maximum likelihood estimation,distance estimation,diffusion,mobile molecular communication
Wiener process,Statistical physics,Molecular communication,Computer science,Maximum likelihood,Stochastic process,Real-time computing,Brownian motion,Probability density function,Channel impulse response,Particle
Conference
ISSN
ISBN
Citations 
2474-9133
978-1-7281-0739-4
0
PageRank 
References 
Authors
0.34
12
6
Name
Order
Citations
PageRank
Shuai Huang121033.05
Lin Lin2206.87
Weisi Guo355060.46
Yan Hao45012.40
Juan Xu561.88
Fuqiang Liu627024.48