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A low-complexity cyclostationary spectrum sensing for Interference Avoidance in
femto-cells LTE-A based Networks
Abstract:
This correspondence focuses on a new spectrum sensing algorithm based on the exploitation of the
primary signal cyclostationarity property, used to avoid the inter-cell interference in a heterogeneous
LTE-A network. The performance of the proposed spectrum sensing method will be evaluated by
means of a suitable analytical approach whose accuracy will be validated by comparing analytical
predictions with simulation results under different communication channel propagation conditions.
Furthermore, it will be shown that the proposed approach requiresthe lowestcomputational complexity
among the cyclostationaritybased methods and allows better performance, even in the case of noise
uncertainty, in terms of false alarm, detection probability and deflection coefficient.

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A low complexity cyclostationary spectrum sensing for interference avoidance in femto-cells lte-a based networks

  • 1. 2020 – 2021 #13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, Vellore – 6. Off: 0416-2247353 Mo: +91 9500218218 / +91 8220150373 Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com A low-complexity cyclostationary spectrum sensing for Interference Avoidance in femto-cells LTE-A based Networks Abstract: This correspondence focuses on a new spectrum sensing algorithm based on the exploitation of the primary signal cyclostationarity property, used to avoid the inter-cell interference in a heterogeneous LTE-A network. The performance of the proposed spectrum sensing method will be evaluated by means of a suitable analytical approach whose accuracy will be validated by comparing analytical predictions with simulation results under different communication channel propagation conditions. Furthermore, it will be shown that the proposed approach requiresthe lowestcomputational complexity among the cyclostationaritybased methods and allows better performance, even in the case of noise uncertainty, in terms of false alarm, detection probability and deflection coefficient.