Paper Info
Title
2-D Channel Characterization of a Molecular Motor Signal
Abstract
In this article, a two-dimensional channel characterization of a molecular motor signal in a diffusive fluid environment is provided by deriving the first hitting time probability density function of the motor signal to an absorbing lattice point. A temporal modulation scheme to establish communication between two nodes using the motor signal is also proposed. Detection of the motor signal is achieved by using the maximum likelihood detector with erasures for a negligible or no-interference scenario. On the other hand, for motor signal reception with inter-symbol interference, the reception process is modeled as a hidden Markov model, and a Viterbi sequence detection algorithm is devised for decoding the sequence of input Markov states. Efficient criteria to determine the memory length of a diffusive molecular communication (MC) system are defined, which address the problem of choosing a detector for a given MC system. It is demonstrated using numerical results that the hitting probability and, consequently, the error performance of the motor signal worsens with an increase in the unbound probability (ϵ/2). Furthermore, it is also quantitatively established, as to, why in nature directed signals are preferred for communication over purely random diffusive signals at larger distances.
Year
DOI
Venue
2020
10.1109/TMBMC.2020.3021293
IEEE Transactions on Molecular, Biological and Multi-Scale Communications
Keywords
DocType
Volume
Active Brownian particle,first hitting time probability density function,hidden Markov model,molecular communication,molecular motor,temporal modulation scheme
Journal
6
Issue
Citations 
PageRank 
2
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Ankit Gupta136236.47
Manav R. Bhatnagar253953.01