Results 301 to 310 of about 4,727,301 (347)

Blind Spectrum Sensing Approaches for Interweaved Cognitive Radio System: A Tutorial and Short Course

IEEE Communications Surveys and Tutorials, 2019
Spectrum sensing is one of the essential tasks to have a cognitive radio system, which will allow an unlicensed user, called secondary user, to utilize the spectrum while the licensed user, called primary user, is not occupying it.
Faroq Awin, Esam Abdel-Raheem, Kemal Tepe   +2 more
exaly   +2 more sources

Hybrid PSO-GSA for energy efficient spectrum sensing in cognitive radio network

Physical Communication, 2020
The Cognitive Radio Network (CRN) in 5G heterogeneous network has trade-off between energy efficiency and spectrum sensing efficiency. Energy Efficiency is important for designing the battery-powered cognitive radio network.
Geoffrey Eappen, S. Thangavelu
semanticscholar   +1 more source

Cooperative Spectrum Sensing Meets Machine Learning: Deep Reinforcement Learning Approach

IEEE Communications Letters, 2020
Cognitive radio network (CRN) emerged to utilize the frequency bands efficiently. To use the frequency bands efficiently without any interference on the licensed user, detection of the frequency holes is the first step, which is called spectrum sensing ...
Rahil Sarikhani, F. Keynia
semanticscholar   +1 more source

Adaptive Multiband Spectrum Sensing

IEEE Wireless Communications Letters, 2012
An adaptive multiband spectrum sensing procedure is developed for fast and reliably locating multiple idle ones among a large number of channels. Through an iterative exploration process to reduce the number of candidate channels, the limited sampling budget can be focused on the more promising locations of the spectrum, resulting in significant ...
Yan Feng, Xiaodong Wang 0001
openaire   +1 more source

Spectrum sensing with multiple antennas

2009 IEEE International Conference on Systems, Man and Cybernetics, 2009
The primary signal detection is an essential operation for the secondary spectrum usage. In this paper we extend the covariance based detection for multiple-antenna receiver. The proposed method uses the noise power estimation and does not suffer from the noise level uncertainty.
Ruttik Kalle, Jäntti Riku, Koufos Konstantinos   +2 more
openaire   +1 more source

Deep CM-CNN for Spectrum Sensing in Cognitive Radio

IEEE Journal on Selected Areas in Communications, 2019
One of the key problems in spectrum sensing is to design the test statistic. Existing methods generally exploit the model-based features as the test statistic, such as energies and eigenvalues.
Chang Liu, Jie Wang, Xuemeng Liu, Ying-Chang Liang   +3 more
semanticscholar   +1 more source

Unsupervised Deep Spectrum Sensing: A Variational Auto-Encoder Based Approach

IEEE Transactions on Vehicular Technology, 2020
In cognitive radio (CR), the test statistics of most spectrum sensing algorithms are generated from the model-based features such as the signal energy and the eigenvalues from the sample covariance matrix (CM).
Jiandong Xie, Jun Fang, Chang Liu, Linxiao Yang   +3 more
semanticscholar   +1 more source

Multiplatform Spectrum Sensing Prototype

2018 IEEE 61st International Midwest Symposium on Circuits and Systems (MWSCAS), 2018
Smart spectrum sharing initiatives have been stimulated by the spectrum scarcity experienced nowadays. The option that secondary users may access idle channels avoiding harmful interferences to primary users is a viable option to alleviate the spectrum crunch.
Danilo Corral-De-Witt, Aarron Younan, Dewan Ariful, Lining Zhang, Kemal Tepe   +4 more
openaire   +1 more source

Deep Cooperative Sensing: Cooperative Spectrum Sensing Based on Convolutional Neural Networks

IEEE Transactions on Vehicular Technology, 2019
In this paper, we investigate cooperative spectrum sensing (CSS) in a cognitive radio network (CRN) where multiple secondary users (SUs) cooperate in order to detect a primary user, which possibly occupies multiple bands simultaneously.
Woongsup Lee, Minhoe Kim, D. Cho
semanticscholar   +1 more source

Robust Spectrum Sensing With Crowd Sensors

IEEE Transactions on Communications, 2014
This paper investigates the issue of cooperative spectrum sensing with a crowd of low-end personal spectrum sensors (such as smartphones, tablets, and in-vehicle sensors), where one critical challenge is the uncertainty of the quality of sensing data from crowd sensors that may be unreliable, untrustworthy, or even malicious.
Guoru Ding, Fei Song 0004, Qihui Wu 0001, Yulong Zou, Linyuan Zhang, Shuo Feng 0001, Jinlong Wang 0001   +6 more
openaire   +1 more source