An Information Theoretic Framework to Analyze Molecular Communication Systems Based on Statistical Mechanics
Tutkimustuotos › › vertaisarvioitu
Standard
An Information Theoretic Framework to Analyze Molecular Communication Systems Based on Statistical Mechanics. / Akyildiz, Ian F.; Pierobon, Massimiliano; Balasubramaniam, Sasitharan.
julkaisussa: Proceedings of the IEEE, Vuosikerta 107, Nro 7, 01.07.2019, s. 1230-1255.Tutkimustuotos › › vertaisarvioitu
Harvard
APA
Vancouver
Author
Bibtex - Lataa
}
RIS (suitable for import to EndNote) - Lataa
TY - JOUR
T1 - An Information Theoretic Framework to Analyze Molecular Communication Systems Based on Statistical Mechanics
AU - Akyildiz, Ian F.
AU - Pierobon, Massimiliano
AU - Balasubramaniam, Sasitharan
N1 - EXT="Akyildiz, Ian F."
PY - 2019/7/1
Y1 - 2019/7/1
N2 - Over the past 10 years, molecular communication (MC) has established itself as a key transformative paradigm in communication theory. Inspired by chemical communications in biological systems, the focus of this discipline is on the modeling, characterization, and engineering of information transmission through molecule exchange, with immediate applications in biotechnology, medicine, ecology, and defense, among others. Despite a plethora of diverse contributions, which has been published on the subject by the research community, a general framework to study the performance of MC systems is currently missing. This paper aims at filling this gap by providing an analysis of the physical processes underlying MC, along with their information-theoretic underpinnings. In particular, a mathematical framework is proposed to define the main functional blocks in MC, supported by general models from chemical kinetics and statistical mechanics. In this framework, the Langevin equation is utilized as a unifying modeling tool for molecule propagation in MC systems, and as the core of a methodology to determine the information capacity. Diverse MC systems are classified on the basis of the processes underlying molecule propagation, and their contribution in the Langevin equation. The classifications and the systems under each category are as follows: random walk (calcium signaling, neuron communication, and bacterial quorum sensing), drifted random walk (cardiovascular system, microfluidic systems, and pheromone communication), and active transport (molecular motors and bacterial chemotaxis). For each of these categories, a general information capacity expression is derived under simplifying assumptions and subsequently discussed in light of the specific functional blocks of more complex MC systems. Finally, in light of the proposed framework, a roadmap is envisioned for the future of MC as a discipline.
AB - Over the past 10 years, molecular communication (MC) has established itself as a key transformative paradigm in communication theory. Inspired by chemical communications in biological systems, the focus of this discipline is on the modeling, characterization, and engineering of information transmission through molecule exchange, with immediate applications in biotechnology, medicine, ecology, and defense, among others. Despite a plethora of diverse contributions, which has been published on the subject by the research community, a general framework to study the performance of MC systems is currently missing. This paper aims at filling this gap by providing an analysis of the physical processes underlying MC, along with their information-theoretic underpinnings. In particular, a mathematical framework is proposed to define the main functional blocks in MC, supported by general models from chemical kinetics and statistical mechanics. In this framework, the Langevin equation is utilized as a unifying modeling tool for molecule propagation in MC systems, and as the core of a methodology to determine the information capacity. Diverse MC systems are classified on the basis of the processes underlying molecule propagation, and their contribution in the Langevin equation. The classifications and the systems under each category are as follows: random walk (calcium signaling, neuron communication, and bacterial quorum sensing), drifted random walk (cardiovascular system, microfluidic systems, and pheromone communication), and active transport (molecular motors and bacterial chemotaxis). For each of these categories, a general information capacity expression is derived under simplifying assumptions and subsequently discussed in light of the specific functional blocks of more complex MC systems. Finally, in light of the proposed framework, a roadmap is envisioned for the future of MC as a discipline.
KW - Fokker-Planck equation
KW - information capacity
KW - Langevin equation
KW - molecular communication (MC)
KW - nanonetworks
KW - Poisson noise
KW - statistical mechanics
U2 - 10.1109/JPROC.2019.2927926
DO - 10.1109/JPROC.2019.2927926
M3 - Article
VL - 107
SP - 1230
EP - 1255
JO - Proceedings of the IEEE
JF - Proceedings of the IEEE
SN - 0018-9219
IS - 7
ER -