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In cognitive radio networks, spectrum sensing is an essential functionality to detect the presence of primary users (PUs). Cyclostationary detector, that can robustly detect weak primary signals, is becoming a promising candidate for spectrum sensing. In this paper, we focus on a weighted cooperative spectrum sensing algorithm based on cyclostationarity. Since the proposed method improves the contributions...
Spectrum sensing is an essential functionality for cognitive radio to improve the utilization ratio of the spectrum. Eigenvalue detector is a promising candidate for spectrum sensing in cognitive radio. However, it requires very long detection time, which leads to inefficient spectrum utilization. In this paper, we propose a new cooperative spectrum sensing algorithm by applying sequential detection...
In this paper, a modified sequential probability ratio test (SPRT) scheme, namely sequential energy detection (SED), is proposed for cooperative spectrum sensing to reduce the average number of required samples. In the scheme, the data samples are first grouped into data blocks and the sequential probability ratio test (SPRT) use the energies of the data blocks as the statistics variables. The resulting...
In cognitive radio networks, multiple cognitive radio nodes perform spectrum sensing cooperatively in order to detect the primary user more accurately. Previous works on cooperative spectrum sensing have shown that the detection performance can be improved through increasing either the observation interval or the number of the sensing nodes. However, increasing the observation interval will result...
In cognitive radio networks, the cognitive radio users can be collaborated to perform spectrum sensing so as to detect the primary user more accurately. However, when the sensing nodes suffer from fading, shadowing, and time-varying nature of wireless channels, it needs to set a long observation time for all of the nodes to make decisions and forward the results to fusion center, which induce the...
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