University of Oulu

E. J. dos Santos, R. D. Souza, J. L. Rebelatto and H. Alves, "Network Slicing for URLLC and eMBB With Max-Matching Diversity Channel Allocation," in IEEE Communications Letters, vol. 24, no. 3, pp. 658-661, March 2020. doi: 10.1109/LCOMM.2019.2959335

Network slicing for URLLC and eMBB with max-matching diversity channel allocation

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Author: dos Santos, Elço João1; Souza, Richard Demo1; Rebelatto, João Luiz2;
Organizations: 1EEL, UFSC, Florianópolis-SC, Brazil
2CPGEI, UTFPR, Curitiba-PR, Brazil
3CWC, University of Oulu, Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.3 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe202001071316
Language: English
Published: Institute of Electrical and Electronics Engineers, 2020
Publish Date: 2020-01-07
Description:

Abstract

This work considers the problem of radio resource sharing between enhanced mobile broadband (eMBB) and ultrareliable and low latency communications (URLLC), two heterogeneous 5G services. More specifically, we propose the use of a max-matching diversity (MMD) algorithm to properly allocate the channels to the eMBB users, considering both heterogeneous orthogonal multiple access (H-OMA) and heterogeneous nonorthogonal multiple access (H-NOMA) network slicing strategies. Our results indicate that MMD can simultaneously improve the eMBB achievable rate and the URLLC reliability regardless the network slicing strategy adopted.

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Series: IEEE communications letters
ISSN: 1089-7798
ISSN-E: 2373-7891
ISSN-L: 1089-7798
Volume: 24
Issue: 3
Pages: 658 - 661
DOI: 10.1109/LCOMM.2019.2959335
OADOI: https://oadoi.org/10.1109/LCOMM.2019.2959335
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
5G
Funding: This work has been supported in Brazil by CNPq and Print CAPES-UFSC “Automation 4.0”, and in Finland by Academy of Finland 6Genesis Flagship (Grant no318927) and EE-IoT (no319008).
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
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