scholarly journals Energy Detection Based Spectrum Sensing for Rural Area Networks

2020 ◽  
Vol 4 (13) ◽  
pp. 163923
Author(s):  
Johanna Vartiainen ◽  
Heikki Karvonen ◽  
Marja Matinmikko-Blue ◽  
Luciano Mendes ◽  
Harri Saarnisaari ◽  
...  
Keyword(s):  
Rural Area ◽  
Spectrum Sensing ◽  
Energy Detection

Spectrum Sensing With High Sensitivity and Interferer Robustness Using Cross-Correlation Energy Detection

2013 ◽  
Vol 3 (4) ◽  
pp. 566-575 ◽  
Author(s):  
Mark S. Oude Alink ◽  
Andre B. J. Kokkeler ◽  
Eric A. M. Klumperink ◽  
Gerard J. M. Smit ◽  
Bram Nauta
Keyword(s):  
Spectrum Sensing ◽  
Cross Correlation ◽  
Correlation Energy ◽  
High Sensitivity ◽  
Energy Detection

Energy Detection Spectrum Sensing with Discontinuous Primary User Signal

2009 ◽  
Author(s):  
F. Penna ◽  
C. Pastrone ◽  
M. A. Spirito ◽  
R. Garello
Keyword(s):  
Spectrum Sensing ◽  
Energy Detection ◽  
Primary User

An Intelligent cognitive sensing and detection strategy for medical telemetry networks

2021 ◽  
pp. 1-10
Author(s):  
S. Surekha ◽  
Md. Zia Ur Rahman
Keyword(s):  
Spectrum Sensing ◽  
Smart Cities ◽  
Cognitive Radios ◽  
False Alarm Probability ◽  
Energy Detection ◽  
Least Mean Square ◽  
Radio Technology ◽  
Smart Hospitals ◽  
Medical Telemetry ◽  
Cognitive Radio Technology

In medical telemetry networks, cognitive radio technology is mostly used to avoid licensed spectrum underutilization and by providing access to unlicensed spectrum users without causing interference to primary users, this concept is widely used in development of smart hospitals and smart cities. In medical telemetry networks frequency spectrum concept is used for providing treatment to patients who are far away from hospitals. In cognitive radios, spectrum sensing concept is used in which energy detection method is mostly used because it is simple to implement. While measuring health care environments using cognitive radios probability detection, false alarm probability and threshold parameters are calculated. In this paper for identifying spectrum holes in spectrum sensing using energy detection, distributed diffusion non-negative least mean square algorithm is proposed. It gives better results compared to energy detection concept alone in terms of probability detection converged earlier. If number of nodes are increasing probability detection is decreased from one and move towards left and its SNR is around 1.5-2 dB with proposed method. Hence simulation results give better results in terms of sensing ability while measuring patient condition.

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