Abstract
A Tactile Internet-based nanonetwork is an emerging field that promises a new range of e-health applications, in which human operators can efficiently operate and control devices at the nanoscale for remote-patient treatment. A haptic feedback is inevitable for establishing a link between the operator and unknown in-body environment. However, haptic communications over the terahertz band may incur significant path loss due to molecular absorption. In this paper, we propose an optimization framework for haptic communications over nanonetworks, in which in-body nanodevices transmit haptic information to an operator via the terahertz band. By considering the properties of the terahertz band, we employ Brownian motion to describe the mobility of the nanodevices and develop a time-variant terahertz channel model. Furthermore, based on the developed channel model, we construct a stochastic optimization problem for improving haptic communications under the constraints of system stability, energy consumption, and latency. To solve the formulated nonconvex stochastic problem, an improved time-varying particle swarm optimization algorithm is presented, which can deal with the constraints of the problem efficiently by reducing the convergence time significantly. The simulation results validate the theoretical analysis of the proposed system.
| Original language | English |
|---|---|
| Article number | 8657743 |
| Pages (from-to) | 3016-3027 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Industrial Informatics |
| Volume | 15 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 2019 May 1 |
Fingerprint
Keywords
- 5G
- e-health
- energy harvesting
- haptic communication
- nanonetwork
- stochastic optimization
- tactile Internet
ASJC Scopus subject areas
- Control and Systems Engineering
- Information Systems
- Computer Science Applications
- Electrical and Electronic Engineering
Cite this
Optimal Haptic Communications Over Nanonetworks for E-Health Systems. / Feng, Li; Ali, Amjad; Iqbal, Muddesar; Bashir, Ali Kashif; Hussain, Syed Asad; Pack, Sangheon.
In: IEEE Transactions on Industrial Informatics, Vol. 15, No. 5, 8657743, 01.05.2019, p. 3016-3027.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Optimal Haptic Communications Over Nanonetworks for E-Health Systems
AU - Feng, Li
AU - Ali, Amjad
AU - Iqbal, Muddesar
AU - Bashir, Ali Kashif
AU - Hussain, Syed Asad
AU - Pack, Sangheon
PY - 2019/5/1
Y1 - 2019/5/1
N2 - A Tactile Internet-based nanonetwork is an emerging field that promises a new range of e-health applications, in which human operators can efficiently operate and control devices at the nanoscale for remote-patient treatment. A haptic feedback is inevitable for establishing a link between the operator and unknown in-body environment. However, haptic communications over the terahertz band may incur significant path loss due to molecular absorption. In this paper, we propose an optimization framework for haptic communications over nanonetworks, in which in-body nanodevices transmit haptic information to an operator via the terahertz band. By considering the properties of the terahertz band, we employ Brownian motion to describe the mobility of the nanodevices and develop a time-variant terahertz channel model. Furthermore, based on the developed channel model, we construct a stochastic optimization problem for improving haptic communications under the constraints of system stability, energy consumption, and latency. To solve the formulated nonconvex stochastic problem, an improved time-varying particle swarm optimization algorithm is presented, which can deal with the constraints of the problem efficiently by reducing the convergence time significantly. The simulation results validate the theoretical analysis of the proposed system.
AB - A Tactile Internet-based nanonetwork is an emerging field that promises a new range of e-health applications, in which human operators can efficiently operate and control devices at the nanoscale for remote-patient treatment. A haptic feedback is inevitable for establishing a link between the operator and unknown in-body environment. However, haptic communications over the terahertz band may incur significant path loss due to molecular absorption. In this paper, we propose an optimization framework for haptic communications over nanonetworks, in which in-body nanodevices transmit haptic information to an operator via the terahertz band. By considering the properties of the terahertz band, we employ Brownian motion to describe the mobility of the nanodevices and develop a time-variant terahertz channel model. Furthermore, based on the developed channel model, we construct a stochastic optimization problem for improving haptic communications under the constraints of system stability, energy consumption, and latency. To solve the formulated nonconvex stochastic problem, an improved time-varying particle swarm optimization algorithm is presented, which can deal with the constraints of the problem efficiently by reducing the convergence time significantly. The simulation results validate the theoretical analysis of the proposed system.
KW - 5G
KW - e-health
KW - energy harvesting
KW - haptic communication
KW - nanonetwork
KW - stochastic optimization
KW - tactile Internet
UR - http://www.scopus.com/inward/record.url?scp=85065420446&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85065420446&partnerID=8YFLogxK
U2 - 10.1109/TII.2019.2902604
DO - 10.1109/TII.2019.2902604
M3 - Article
AN - SCOPUS:85065420446
VL - 15
SP - 3016
EP - 3027
JO - IEEE Transactions on Industrial Informatics
JF - IEEE Transactions on Industrial Informatics
SN - 1551-3203
IS - 5
M1 - 8657743
ER -