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A Blind Spatial Spectrum Sensing Algorithm for Noncircular Signals
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AI
DOI：10.1109/LCOMM.2025.3539762.png)
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Abstract
En 中文
In cognitive radio, most spatial spectrum sensing algorithms ignore the characteristic of the noncircular (NC) signals that are common in modern communication systems. In this letter, we propose a novel blind spatial spectrum sensing algorithm for NC signals. First, the spatial spectrum of the NC signals is improved by utilizing the complementary covariance. On this basis, we present the maximum-minimum spatial spectrum of the NC signals (NC-MMSS) detection, which can detect the signal of primary user (PU) and provide corresponding angle of arrival (AoA) information. Then the theoretical expressions of probability of false alarm, decision threshold, and probability of detection are derived. Finally, simulation results verify that the proposed method is superior to the existing spatial spectrum sensing algorithms.
Keywords:
Sensors
Vectors
Covariance matrices
Signal to noise ratio
Standards
Binary phase shift keying
Training
Probability
Power generation
Interference
Cognitive radio
spatial spectrum sensing
noncircular signal
complementary covariance
Journal
IF:
4.4
Papers:
1.3W
Citations:
2.2W