Gaussianity Testing as an Effective Technique for Detecting Discontinuous Transmission in 5G Networks
| Autor: | Mieczyslaw Jessa, Jakub Nikonowicz |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
General Computer Science
Computer science discontinuous transmission 02 engineering and technology Communications system Signal-to-noise ratio 0502 economics and business 0202 electrical engineering electronic engineering information engineering Electronic engineering General Materials Science Detection theory Discontinuous transmission energy detection 05 social sciences Transmitter Detector General Engineering Gaussianity testing 020206 networking & telecommunications Cognitive radio Transmission (telecommunications) Probability distribution lcsh:Electrical engineering. Electronics. Nuclear engineering lcsh:TK1-9971 050203 business & management Energy (signal processing) |
| Zdroj: | IEEE Access, Vol 9, Pp 22186-22194 (2021) |
| ISSN: | 2169-3536 |
| Popis: | The paper investigates statistical distribution testing-based detection methods in an intermittent signal detection scenario. The relevance of the research is driven by 5G networks based on packet transmission, incorporating the concept of cognitive radio and adapting spectrum detection methods from Long Term Evolution (LTE) Licensed-Assisted Access (LAA). The conducted study refers to the recently proposed methods based on testing goodness-of-fit (GoF) of statistical distributions, which are compared with a conventional energy detector. The authors examine the applicability of well-known GoF methods in intermittent transmission, as they require reconsideration in 5G communication systems, and investigate the behavior of the innovative energy-based GoF. The experiments are carried out for different transmitter activity factors, i.e., channel occupancy and signal-to-noise ratio (SNR), demonstrating the superiority of the GoF-based methods in general and particularly the invented GoF test over other energy-based detectors for discontinuous signals detection. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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