Research Article
A Novel DAG Spectrum Sensing Algorithm with Reducing Computational Complexity
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@INPROCEEDINGS{10.1007/978-3-030-14657-3_46, author={Weiting Gao and Fuwei Jiang and Fei Ma and Weilun Liu}, title={A Novel DAG Spectrum Sensing Algorithm with Reducing Computational Complexity}, proceedings={IoT as a Service. 4th EAI International Conference, IoTaaS 2018, Xi’an, China, November 17--18, 2018, Proceedings}, proceedings_a={IOTAAS}, year={2019}, month={3}, keywords={Eigenvalue Spectrum sensing Arithmetic mean Geometric mean Computational complexity DMM}, doi={10.1007/978-3-030-14657-3_46} }- Weiting Gao
Fuwei Jiang
Fei Ma
Weilun Liu
Year: 2019
A Novel DAG Spectrum Sensing Algorithm with Reducing Computational Complexity
IOTAAS
Springer
DOI: 10.1007/978-3-030-14657-3_46
Abstract
Aiming at problems that the eigenvalue based spectrum sensing algorithms don’t perform well in the situation of low SNR, small sample and need high computational complexity with eigenvalue decomposition, based on the difference value between maximum and minimum eigenvalue spectrum sensing algorithm (DMM), a difference value between the arithmetic mean and geometric mean eigenvalue spectrum sensing algorithm (DAG) with low computational complexity and dynamic threshold was proposed, which via the power method. Simulation results show that the DAG can improve performance over the classical algorithms in situation of low SNR, small samples and increased second users without reduction of computational complexity.
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