Title
A Sensitivity Analysis on the Potential of 5G Channel Quality Prediction
Author
Anbalagan, S.N.
Litjens, R.
Das, K.
Chiumento, A.
Havinga, A,
van den Berg, H.
Publication year
2021
Abstract
With increasing network complexity, intelligent mechanisms to efficiently achieve the required quality of service of wireless-enabled applications are being developed, especially for industrial environments due to the onset of the fourth industrial revolution. In this paper, the potential benefits of wireless channel quality prediction for two of the three major use cases supported by 5G viz. enhanced Mobile BroadBand (eMBB) and Ultra-Reliable Low Latency Communication (URLLC) are quantified in an industrial indoor environment through simulations. Our analysis shows that the ability to perform perfect prediction improves the 10 th user throughput percentile by up to 125% for eMBB use case and decreases the 90 th resource utilization percentile by up to 37% for URLLC use case. Furthermore, the maximum tolerable prediction inaccuracy is found to be up to 5 dB and 0.35 dB for eMBB and URLLC use cases, respectively.
Subject
Industrial IoT
Networking
Factories of the Future
5G
To reference this document use:
http://resolver.tudelft.nl/uuid:571280e8-db06-441b-8522-3b9facac7999
TNO identifier
957170
Publisher
IEEE
Source
2021 25-28 April IEEE 93rd Vehicular Technology Conference
Document type
conference paper