Multiband Spectrum Sensing Based on the Sample Entropy

Author:

Molina-Tenorio Yanqueleth,Prieto-Guerrero AlfonsoORCID,Aguilar-Gonzalez RafaelORCID

Abstract

Cognitive radios represent a real alternative to the scarcity of the radio spectrum. One of the primary tasks of these radios is the detection of possible gaps in a given bandwidth used by licensed users (called also primary users). This task, called spectrum sensing, requires high precision in determining these gaps, maximizing the probability of detection. The design of spectrum sensing algorithms also requires innovative hardware and software solutions for real-time implementations. In this work, a technique to determine possible primary users’ transmissions in a wide frequency interval (multiband spectrum sensing) from the perspective of cognitive radios is presented. The proposal is implemented in a real wireless communications environment using low-cost hardware considering the sample entropy as a decision rule. To validate its feasibility for real-time implementation, a simulated scenario was first tested. Simulation and real-time implementations results were compared with the Higuchi fractal dimension as a decision rule. The encouraging results show that sample entropy correctly detects noise or a possible primary user transmission, with a probability of success around 0.99, and the number of samples with errors at the start and end of frequency edges of transmissions is, on average, only 12 samples.

Publisher

MDPI AG

Subject

General Physics and Astronomy

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Development of Logistic regression based spectrum sensing algorithm using extreme eigenvalues;2023 International Conference in Advances in Power, Signal, and Information Technology (APSIT);2023-06-09

2. Cooperative Multiband Spectrum Sensing Using Radio Environment Maps and Neural Networks;Sensors;2023-05-30

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