University of Oulu

C. Padilla, R. Hashemi, N. H. Mahmood and M. Latva-Aho, "A Nonlinear Autoregressive Neural Network for Interference Prediction and Resource Allocation in URLLC Scenarios," 2021 International Conference on Information and Communication Technology Convergence (ICTC), 2021, pp. 184-189, doi: 10.1109/ICTC52510.2021.9620845.

A nonlinear autoregressive neural network for interference prediction and resource allocation in URLLC scenarios

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Author: Padilla, Christian1; Hashemi, Ramin1; Mahmood, Nurul Huda1;
Organizations: 1Centre for Wireless Communications (CWC), University of Oulu, Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.6 MB)
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Language: English
Published: Institute of Electrical and Electronic Engineers, 2021
Publish Date: 2023-01-03


Ultra reliable low latency communications (URLLC) is a new service class introduced in 5G which is characterized by strict reliability (1–10 −5) and low latency requirements (1 ms). To meet these requisites, several strategies like overprovisioning of resources and channel-predictive algorithms have been developed. This paper describes the application of a Nonlinear Autoregressive Neural Network (NARNN) as a novel approach to forecast interference levels in a wireless system for the purpose of efficient resource allocation. Accurate interference forecasts also grant the possibility of meeting specific outage probability requirements in URLLC scenarios. Performance of this proposal is evaluated upon the basis of NARNN predictions accuracy and system resource usage. Our proposed approach achieved a promising mean absolute percentage error of 7.8 % on interference predictions and also reduced the resource usage in up to 15 % when compared to a recently proposed interference prediction algorithm.

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Series: International Conference on Information and Communication Technology Convergence
ISSN: 2162-1233
ISSN-E: 2162-1241
ISSN-L: 2162-1233
ISBN: 978-1-6654-2383-0
ISBN Print: 978-1-6654-2384-7
Pages: 184 - 189
DOI: 10.1109/ICTC52510.2021.9620845
Host publication: 12th International Conference on Information and Communication Technology Convergence, ICTC 2021
Conference: International Conference on Information and Communication Technology Convergence
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This work was supported by the Academy of Finland 6Genesis Flagship project under grant 318927.
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
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