Cooperative spectrum sensing based on a modified shuffled frog leaping algorithm in 5G network-Reference-Cited by-同舟云学术

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Cooperative spectrum sensing based on a modified shuffled frog leaping algorithm in 5G network

Published:2017-12 Issue: Volume:25 Page:438-444
ISSN:1874-4907
Container-title:Physical Communication
language:en
Short-container-title:Physical Communication

Author:

Tong Xunqian,Ji Yanju,Lin Jun,Zhu Jinbao,Sun Feng,Zhong Yi,Yang Yang,Zhu Xi

Funder

China Postdoctoral Science Foundation

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering

Reference20 articles.

1. Cognitive radio spectrum sensing framework based on multi-agent architecture for 5G networks;Zhang;IEEE wirel. commun.,2015

2. A spectrum handoff scheme for optimal network selection in cognitive radio vehicular networks: a game theoretic auction theory approach;Kumar;Physical Communication,2017

3. Capacity-aware cooperative spectrum sensing based on noise power estimation;Rakovic;IEEE Trans. Commun.,2015

4. Cognitive radio: brain-empowered wireless communications;Haykin;IEEE J. Sel. Area. Comm.,2005

5. Multiuser detection for the uplink of clustered 5G systems with universal frequency reuse;Ribeiro;Physical Communication,2017

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1. DOA Estimation Based on Gridless Fuzzy Active Learning Under Unknown Mutual Coupling and Nonuniform Noise: Experimental Verification;IEEE Sensors Journal;2023-07-15

2. On eigenvalue-based cooperative spectrum sensing using feature extraction and maximum entropy fuzzy clustering;Journal of Ambient Intelligence and Humanized Computing;2022-01-27

3. Quality of service optimization in orthogonal frequency division multiplexing‐based cognitive radio systems based on shuffled frog leaping algorithm;Concurrency and Computation: Practice and Experience;2021-10-18

4. A Wideband 5G Cyclostationary Spectrum Sensing Method by Kernel Least Mean Square Algorithm for Cognitive Radio Networks;IEEE Transactions on Circuits and Systems II: Express Briefs;2021-07

5. Eigenvalue-based cooperative spectrum sensing using kernel fuzzy c-means clustering;Digital Signal Processing;2021-04

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