An Adaptive Algorithm for Energy Detection in Cognitive Radio Networks

Cognitive radio is a modern wireless communication methodology that deals with the issue of spectrum untapped. Cognitive users can continually perceive the licensed spectrum to hunt for unoccupied spots. The essential technology in cognitive radio (CR) for primary user detection is spectrum sensing. Due to signal to noise ratio (SNR), noise uncertainty in spectrum sensing would make the detection unreliable. In this paper, the two adaptive thresholds based on_covariance absolute values (TATCAV) are proposed to increase detection performance in the presence of noise uncertainty. According to the computer simulations using MATLAB 2021b, the value of the probability of detection is Pd=98.1% Compared with the results of two thresholds based on_covariance absolute values (TTCAV) Pd= 95.3% at SNR=-18, noise uncertainty Nu=1.761 dB, and using quadrature amplitude modulation (QAM). And the error rate for the proposed approach is Pe=12.1% under the same circumstances. The proposed approach results, according to the simulations, are considerably better than the results of the fixed two-threshold approach.

show abstract

“…𝜎 𝑥 2 is the signal variance, and 𝜎 𝜔 2 Variation in noise, , and 𝛾 is the threshold decision, N number of samples [27].…”

Section: Methods 21 System Modelmentioning

confidence: 99%

Covariance absolute values spectrum sensing method based on two adaptive thresholds

Hashim

Ziboon

Abdulsatar

2023

IJEECS

View full text Add to dashboard Cite

show abstract

“…Hence it is essential to take into consideration all the tradeoffs when setting the threshold for the energy detection scheme [10]. Let us quantify the received signal 𝑦(𝑛), a random variable, in the form of a binary hypothesis as shown below [8]:…”

Section: System Modelmentioning

confidence: 99%

“…Many of these schemes have been proposed in literature and rely on parameters like spectrum width [1], signal interference and noise ratio (SINR), spectral efficiency and weight factor [8], etc. In this paper, we analyze and evaluate the performance of a SNR estimation based algorithm for adaptive and smart energy detection for spectrum sensing.…”

Section: Introductionmentioning

confidence: 99%

Implementation of SNR estimation based energy detection on USRP and GNU radio for cognitive radio networks

Talukdar

Mehta

Aggrawal

et al. 2017

2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)

View full text Add to dashboard Cite

Development of smart spectrum sensing techniques is the most important task in the design of a cognitive radio system which uses the available spectrum efficiently. The adaptive SNR estimation based energy detection technique has the dual benefit of improving the efficiency of spectrum usage by capitalizing on the underutilization of the spectrum in an adaptive and iterative fashion, as well as reducing the hardware resources leading to easy implementation on a versatile and diverse group of cognitive radio infrastructures. The use of adaptive threshold for energy detection based on SNR estimation improves the spectrum sensing performance and efficiency of the cognitive radio by many folds, especially in low SNR as well as high noise variance situations. The proposed method is implemented on the USRP B200 and results show significant improvement in the detection rate of primary users as compared to conventional energy detection techniques.

show abstract

A modified three-event energy detection scheme using decision threshold optimization for sensing performance improvement in a cognitive radio system

2023

View full text Add to dashboard Cite

An Adaptive Algorithm for Energy Detection in Cognitive Radio Networks

Cited by 7 publications

References 7 publications

Covariance absolute values spectrum sensing method based on two adaptive thresholds

Covariance absolute values spectrum sensing method based on two adaptive thresholds

Implementation of SNR estimation based energy detection on USRP and GNU radio for cognitive radio networks

A modified three-event energy detection scheme using decision threshold optimization for sensing performance improvement in a cognitive radio system

Contact Info

Product

Resources

About