JOURNAL ARTICLE

Research on cooperative spectrum sensing algorithm based on data fusion

Abstract

In view of the actual wireless communication environment, there exists the difference between different location of the cognitive radio spectrum sensing node. This paper studies excellent detection performance of each node spectrum sensing of cognitive level in different conditions of received signal to noise ratio. The data fusion criteria which cognitive user adopt under different SNR could take directly affects the overall cooperative spectrum sensing detection performance, and there have cognitive fusion nodes with lower SNR to be in confluence, on the contrary it will reduce the overall detection performance. Therefore the hybrid data fusion based cooperative spectrum sensing algorithm is proposed, the method based on different SNR classifies cognitive nodes. The different criteria for data fusion is taken according to each type of the characteristics. It can be proved to improve the detection performance of the whole system effectively through MATLAB simulation in different channel environments.

Keywords:
Cognitive radio Computer science Node (physics) Sensor fusion Signal-to-noise ratio (imaging) Channel (broadcasting) Fusion MATLAB Wireless Fusion center Spectrum (functional analysis) Algorithm Noise (video) Real-time computing Artificial intelligence Computer network Telecommunications Engineering

Metrics

4
Cited By
0.36
FWCI (Field Weighted Citation Impact)
6
Refs
0.72
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cognitive Radio Networks and Spectrum Sensing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Distributed Sensor Networks and Detection Algorithms
Physical Sciences →  Computer Science →  Computer Networks and Communications
Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence

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