I. Muhammad, H. Alves, N. H. Mahmood, O. L. A. López and M. Latva-aho, "Mission Effective Capacity—A Novel Dependability Metric: A Study Case of Multiconnectivity-Enabled URLLC for IIoT," in IEEE Transactions on Industrial Informatics, vol. 18, no. 6, pp. 4180-4188, June 2022, doi: 10.1109/TII.2021.3103406
Mission effective capacity: a novel dependability metric : a study case of multiconnectivity-enabled URLLC for IIoT
|Author:||Muhammad, Irfan1; Alves, Hirley1; Mahmood, Nurul Huda1;|
1Centre for Wireless Communications, University of Oulu, 90570 Oulu, Finland
|Online Access:||PDF Full Text (PDF, 1 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2022082956586
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2022-08-29
Various industrial Internet of Things applications demand execution periods throughout which no communication failure is tolerated. However, the classical understanding of reliability in the context of ultra-reliable low-latency communication (URLLC) does not reflect on the time-varying characteristics of the wireless channel. In this article, we introduce a novel mission reliability and mission effective capacity metric that takes these phenomena medium into account, while specifically studying multiconnectivity (MC)-enabled industrial radio systems. We assume uplink short packet transmission with no channel state information at URLLC user (the transmitter) and sporadic traffic arrival. Moreover, we leverage the existing framework of dependability theory and provide closed-form expressions (CFEs) for the mission reliability of the MC system using the maximal-ratio combining scheme. We do so by utilizing the mean time to first failure, which is the expected time of failure occurring for the first time. Moreover, we also derive exact CFEs for second-order statistics, such as level crossing rate and average fade duration, showing how fades are distributed in fading channels with respect to time. Furthermore, the design throughput maximization problem under the mission reliability constraint is solved numerically through the cross-entropy method.
IEEE transactions on industrial informatics
|Pages:||4180 - 4188|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work was supported bythe Academy of Finland through 6Genesis Flagship under Grant 318937 and through EE-IoT Project under Grant 319008.
|Academy of Finland Grant Number:||
319008 (Academy of Finland Funding decision)
© The Author(s) 2022. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0.