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Open AccessArticle

Centralized Co-Operative Detection Algorithm Based on Double Thresholds for Underwater Acoustic Networks

by Jing Zhang, Qiqi Wang and Rui Zhang

Appl. Sci. 2023, 13(5), 3339; https://doi.org/10.3390/app13053339 - 6 Mar 2023

Cited by 1 | Viewed by 1610

Spectrum-sensing algorithms are one of the effective solutions to the problem of the underwater spectrum resource constraint. However, because the underwater acoustic channel is one of the most complex channels, it has many characteristics, such as a limited communication bandwidth, multipath effect, and ocean noise, all of which render the spectrum detection more difficult. As basic spectrum-sensing algorithms, energy detection algorithms are widely used in underwater acoustic communication and radio. However, most of the existing dual-threshold energy detection methods do not judge the signals with energy values between the thresholds or discard them directly. In this paper, a double-threshold centralized co-operative detection algorithm is proposed to solve this problem. In this algorithm, each sensing user makes a judgment independently, and if the historical energy statistics are between the thresholds, the number of sampling points is increased, and the judgment is made again. In the centralized collaborative sensing algorithm, each sensing user’s results are sent to the fusion center, which uses the OR judgment criterion to make decisions. Simulation results show that this algorithm can improve the detection performance and reduce the error rate. Full article

(This article belongs to the Special Issue Underwater Acoustic Communications and Sensor Networks)

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15 pages, 2440 KiB

Open AccessArticle

Dual Threshold Cooperative Sensing Based Dynamic Spectrum Sharing Algorithm for Integrated Satellite and Terrestrial System

by Mingchuan Yang, Guanchang Xue, Botao Liu and Yupu Yang

Remote Sens. 2022, 14(23), 6061; https://doi.org/10.3390/rs14236061 - 29 Nov 2022

Cited by 1 | Viewed by 2061

Abstract

In this paper, cognitive technology is introduced into the integrated satellite terrestrial system to realize the dynamic spectrum sharing of the system and improve the utilization rate of spectrum resources. To overcome the effects of low signal-to-noise ratio (SNR) and noise uncertainty in the channel, a dual-threshold cooperative sensing strategy based on energy detection is introduced. Spectrum sensing is considered as a binary hypothesis problem, but the uncertainty of noise interference in the integrated satellite terrestrial cognitive system will cause the perception to appear ambiguous. Moreover, the noise power varies with time and relative position within a certain range. In the fuzzy state, the perception technology adopts the equal-gain merging algorithm, and derives the voting optimization algorithm to improve the accuracy of decision-making. In addition, taking the minimum error probability as the optimization goal, the optimal adjustment of the adaptive double threshold is realized based on the equal-gain combining algorithm. The simulation results show that the spectrum detection accuracy under low SNR is improved, and the opportunity for terrestrial networks to share spectrum resources is increased. Full article

(This article belongs to the Special Issue Multiple Access Edge Computing in Non-Terrestial and Terrestrial Internet of Things Networks)

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