Parisa Nouri, Hirley Alves, Mikko A. Uusitalo, Onel Alcaraz López, Matti Latva-aho, Machine-type wireless communications enablers for beyond 5G: Enabling URLLC via diversity under hard deadlines, Computer Networks, Volume 174, 2020, 107227, ISSN 1389-1286, https://doi.org/10.1016/j.comnet.2020.107227
Machine-type wireless communications enablers for beyond 5G : enabling URLLC via diversity under hard deadlines
|Author:||Nouri, Parisa1; Alves, Hirley1; Uusitalo, Mikko A.2;|
16G Flagship, Centre for Wireless Communications (CWC), University of Oulu, Finland
2Nokia Bell Labs, Espoo, Finland
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2020050725584
|Publish Date:|| 2022-03-27
URLLC is a key design aim in 5G and a mandatory prerequisite in the future uncountable number of industrial applications. In this regard, cooperative relaying and diversity sources in time and frequency domains are introduced as URLLC enablers to support higher reliability and lower latency. The objective of this work is to study two URLLC performance metrics namely, probability of time underflow where the aggregated transmission time is below the time threshold, and reliability which refers to successfully delivering the message within the time window. We examine the impact of cooperative relaying and exploiting time and frequency diversities on the aforementioned performance metrics. We provide the approximated upper bound of the probability of time underflow under time and frequency diversities. In addition, we indicate the maximum achievable reliability as a function of the time threshold for a given probability of time underflow. The performance advantage of cooperative diversity compared to the single transmission to meet URLLC requirements is also highlighted.
Computer networks. The international journal of computer and telecommunications networking
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This research has been financially supported by Academy of Finland, 6Genesis Flagship (Grant no318927), Aka Prof (no 307492), and Nokia Bell Labs (project UEBE).
|Academy of Finland Grant Number:||
318927 (Academy of Finland Funding decision)
307492 (Academy of Finland Funding decision)
© 2020 Elsevier B.V. All rights reserved. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.