University of Oulu

S. Ishihara, K. Umebayashi and J. Lehtomäki, "Energy Detection for M-QAM Signals," 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), 2021, pp. 1-5, doi: 10.1109/VTC2021-Spring51267.2021.9448730

Energy detection for M-QAM signals

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Author: Ishihara, Shun1; Umebayashi, Kenta1; Lehtomäki, Janne2
Organizations: 1Faculty of Engineering Tokyo University of Agriculture and Technology Tokyo, Japan
2Centre for Wireless Communications University of Oulu Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.3 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2021
Publish Date: 2021-10-21


In this paper, we address energy detection for M-ary quadrature amplitude modulation (QAM) signals. In the literature deterministic signal model is widely used and detection probability is a function of signal energy. Unlike constant amplitude signals, the QAM signal is not deterministic since the energy in each QAM symbol can randomly vary. For random signals, model where both signal and noise are Gaussian has been widely used. However, this approximation may not provide accurate detection probability for QAM signals. Instead the detection probability should be averaged over the distribution of the energy. Previous work has considered calculating exact detection probability for given M analytically. However, the method presented previously has complexity that increases as a function of M and the number of samples. In this paper, we show that the distribution of observed energy for any M can be accurately approximated by one distribution which is derived analytically. Multiple numerical results showing probability density function, Kolmogorov-Smirnov distance, and detection probability are shown. Based on these results, a range where the proposed approximation is applicable is obtained.

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Series: IEEE Vehicular Technology Conference
ISSN: 1090-3038
ISSN-L: 1090-3038
ISBN: 978-1-7281-8964-2
ISBN Print: 978-1-7281-8965-9
Article number: 9448730
DOI: 10.1109/VTC2021-Spring51267.2021.9448730
Host publication: 93rd IEEE Vehicular Technology Conference, VTC 2021-Spring
Conference: IEEE Vehicular Technology Conference
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 European Commission in the framework of the H2020-EUJ-02-2018 project 5GEnhance (Grant agreement no. 815056), by “Strategic Information and Communications R&D Promotion Programme (SCOPE)” of Ministry of Internal Affairs and Communications (MIC) of Japan (Grant no. JPJ000595), the JSPS KAKENHI Grant Numbers JP18K04124 and JP18KK0109, and Institute of Global Innovation Research in TUAT. The work of J. Lehtom¨aki was supported by the Academy of Finland 6Genesis Flagship.
EU Grant Number: (815056) 5G-Enhance - 5G Enhanced Mobile Broadband Access Networks in Crowded Environments
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