Multi-service Signal Multiplexing and Isolation for Physical-Layer Network Slicing (PNS)

Zhang, L. , Ijaz, A., Mao, J., Xiao, P. and Tafazolli, R. (2018) Multi-service Signal Multiplexing and Isolation for Physical-Layer Network Slicing (PNS). In: 2017 IEEE 86th Vehicular Technology Conference: VTC2017-Fall, Toronto, ON, Canada, 24-27 Sep 2017, ISBN 9781509059355 (doi: 10.1109/VTCFall.2017.8288105)

143640.pdf - Accepted Version



Network slicing has been identified as one of the most important features for 5G and beyond to enable operators to utilize networks on an as-a-service basis and meet the wide range of use cases. In physical layer, the frequency and time resources are split into slices to cater for the services with individual optimal designs, resulting in services/slices having different baseband numerologies (e.g., subcarrier spacing) and / or radio frequency (RF) front-end configurations. In such a system, the multi-service signal multiplexing and isolation among the service/slices are critical for the Physical-Layer Network Slicing (PNS) since orthogonality is destroyed and significant inter-service/ slice-band-interference (ISBI) may be generated. In this paper, we first categorize four PNS cases according to the baseband and RF configurations among the slices. The system model is established by considering a low out of band emission (OoBE) waveform operating in the service/slice frequency band to mitigate the ISBI. The desired signal and interference for the two slices are derived. Consequently, one-tap channel equalization algorithms are proposed based on the derived model. The developed system models establish a framework for further interference analysis, ISBI cancelation algorithms, system design and parameter selection (e.g., guard band), to enable spectrum efficient network slicing.

Item Type:Conference Proceedings
Keywords:Network slicing, physical layer network slicing (PNS), inter-service / slice-band-interference (ISBI), isolation and multiplexing, waveform, multi-service.
Glasgow Author(s) Enlighten ID:Zhang, Professor Lei
Authors: Zhang, L., Ijaz, A., Mao, J., Xiao, P., and Tafazolli, R.
College/School:College of Science and Engineering > School of Engineering
Journal Name:VTC2017-Fall Proceedings
Copyright Holders:Copyright © 2017 IEEE
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher
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