2020
DOI: 10.4108/eai.7-4-2020.163923
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Energy Detection Based Spectrum Sensing for Rural Area Networks

Abstract: Remote and rural areas are a challenge to deploy cost-efficient connectivity solutions. 5G technology needs lower frequencies, which calls for spectrum sharing for local networks. Spectrum sensing could complement traditional database approach for spectrum sharing in these areas. This paper studies a windowing based (WIBA) blind spectrum sensing method and compares its performance to a localization algorithm based on double-thresholding (LAD). Both methods are based on energy detection and can be used in any b… Show more

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Cited by 2 publications
(2 citation statements)
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References 25 publications
(35 reference statements)
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“…The User Equipment (UE) can be instructed by the base station to perform a spectrum measurement at its location infers whether the channel is available or occupied. The Collaborative Spectrum Sensing Optimized for Remote Areas [ 25 ] block acquires samples collected from the channel and each requested UE performs a Primary User detection algorithm. The outcome of this measurement is one of two hypotheses: H0, stating that the channel is available or H1, stating that the channel is occupied.…”
Section: Background On 5g-range Technologiesmentioning
confidence: 99%
“…The User Equipment (UE) can be instructed by the base station to perform a spectrum measurement at its location infers whether the channel is available or occupied. The Collaborative Spectrum Sensing Optimized for Remote Areas [ 25 ] block acquires samples collected from the channel and each requested UE performs a Primary User detection algorithm. The outcome of this measurement is one of two hypotheses: H0, stating that the channel is available or H1, stating that the channel is occupied.…”
Section: Background On 5g-range Technologiesmentioning
confidence: 99%
“…The proposed approach was developed using a blind signal estimation approach, which enhanced the energy detection performance. In [5] for multipath and multi-channel conditions a window-based blind spectrum estimation is proposed. This approach also improved the energy detection performance and hence the spectrum sensing in cognitive radio.…”
mentioning
confidence: 99%