University of Oulu

Vartiainen J., Karvonen H., Matinmikko-Blue M., Mendes L. (2019) Performance Evaluation of Windowing Based Energy Detector in Multipath and Multi-signal Scenarios. In: Kliks A. et al. (eds) Cognitive Radio-Oriented Wireless Networks. CrownCom 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 291. Springer, Cham

Performance evaluation of windowing based energy detector in multipath and multi-signal scenarios

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Author: Vartiainen, Johanna1; Karvonen, Heikki1; Matinmikko-Blue, Marja1;
Organizations: 1Centre for Wireless Communications, University of Oulu, Finland
2Radiocommunications Research Center, Inatel, Brazil
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.5 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019121949070
Language: English
Published: Springer Nature, 2019
Publish Date: 2019-12-19
Description:

Abstract

Connectivity in remote areas continues to be a major challenge despite of the evolution of cellular technology. 5th Generation (5G) technology can address remote connectivity if lower carrier frequencies are available, which calls for shared use of spectrum to enable cost-efficient license-free solution. Therefore, spectrum sensing has its own role in future wireless systems such as mobile 5G networks and Internet of Things (IoT) to complement database approach in dynamic spectrum utilization. In this paper, a windowing based (WIBA) blind spectrum sensing method is studied. Its performance is compared to the localization algorithm based on double-thresholding (LAD) detection method. Both the methods are based on energy detection and can be used in any frequency range as well as for detecting all kind of relatively narrowband signals. Probability of detection, relative mean square error for the bandwidth estimation, and the number of detected signals were evaluated, including multipath and multi-signal scenarios. The simulation results show that the WIBA method is very suitable for future 5G applications especially for remote area connectivity, due to its good detection performance in low signal-to-noise ratio (SNR) areas with low complexity and reasonable costs. The simulation results also show importance of the used detection window selection since too wide detection window degrades the detection performance of the WIBA method.

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Series: Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
ISSN: 1867-8211
ISSN-E: 1867-822X
ISSN-L: 1867-8211
ISBN: 978-3-030-25748-4
ISBN Print: 978-3-030-25747-7
Pages: 59 - 72
DOI: 10.1007/978-3-030-25748-4_5
OADOI: https://oadoi.org/10.1007/978-3-030-25748-4_5
Host publication: Cognitive Radio-Oriented Wireless Networks 14th EAI International Conference, CrownCom 2019, Poznan, Poland, June 11–12, 2019, Proceedings
Conference: International Conference on Cognitive Radio Oriented Wireless Networks
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Funding: This research has received funding from the European Union Horizon 2020 Programme (H2020/2017–2019) under grant agreement N0. 777137 and from the Ministry of Science, Technology and Innovation of Brazil through Rede Nacional de Ensino e Pesquisa (RNP) under the 4th EU-BR Coordinated Call Information and Communication Technologies through 5G-RANGE project. In addition, this research has been financially supported in part by Academy of Finland 6Genesis Flagship (grant 318927) and CNPq-Brasil.
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
Copyright information: © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019. This is a post-peer-review, pre-copyedit version of an article published in Cognitive Radio-Oriented Wireless Networks 14th EAI International Conference, CrownCom 2019, Poznan, Poland, June 11–12, 2019, Proceedings. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-25748-4_5.