University of Oulu

M. Shehab, H. Alves and M. Latva-aho, "Effective Capacity and Power Allocation for Machine-Type Communication," in IEEE Transactions on Vehicular Technology. doi: 10.1109/TVT.2019.2900580

Effective capacity and power allocation for machine-type communication

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Author: Shehab, Mohammad1; Alves, Hirley1; Latva-aho, Matti1
Organizations: 1Centre for Wireless Communications (CWC), University of Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.6 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019041612531
Language: English
Published: Institute of Electrical and Electronics Engineers, 2019
Publish Date: 2019-04-16
Description:

Abstract

Effective capacity (EC) determines the maximum communication rate subject to a particular delay constraint. In this work, we analyze the EC of ultra reliable Machine Type Communication (MTC) networks operating in the finite blocklength (FB) regime. First, we present a closed form approximation for EC in quasi-static Rayleigh fading channels. Our analysis determines the upper bounds for EC and delay constraint when varying transmission power. Finally, we characterize the power-delay trade-off for fixed EC and propose an optimum power allocation scheme which exploits the asymptotic behavior of EC in the high SNR regime. The results illustrate that the proposed scheme provides significant power saving with a negligible loss in EC.

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Series: IEEE transactions on vehicular technology
ISSN: 0018-9545
ISSN-E: 1939-9359
ISSN-L: 0018-9545
Volume: 68
Issue: 4
Pages: 4098 - 4102
DOI: 10.1109/TVT.2019.2900580
OADOI: https://oadoi.org/10.1109/TVT.2019.2900580
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Funding: This work is partially supported by Academy of Finland 6Genesis Flagship (Grant no. 318927), Aka Project EE-IoT (Grant no. 319008), and by Finnish Funding Agency for Technology and Innovation (Tekes), Bittium Wireless, Keysight Technologies Finland, Kyynel, MediaTek Wireless, and Nokia Solutions and Networks.
Academy of Finland Grant Number: 318927
319008
Detailed Information: 318927 (Academy of Finland Funding decision)
319008 (Academy of Finland Funding decision)
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