An New Optimal Decision Threshold Criterion for Broadband-Based Energy Detection with Performance Constraints

2013 ◽  
Vol 765-767 ◽  
pp. 2242-2249
Author(s):  
Wen Wen Liu ◽  
Long Yuan ◽  
Zi Yang Liu ◽  
Tao Peng ◽  
Wen Bo Wang
Keyword(s):  
False Alarm ◽  
Spectrum Sensing ◽  
Spectrum Sharing ◽  
Closed Form Solution ◽  
Energy Detection ◽  
Detection Algorithm ◽  
Observation Time ◽  
Optimal Decision ◽  
Decision Threshold ◽  
Threshold Criterion

We study on the energy detection algorithm of spectrum sensing. The performance of energy detection in spectrum sensing is measured by the false alarm probability and the missing detection probability. In a certain spectrum sharing environment, whether the energy detection algorithm can meet our requirement is depending on the length of observation time and the decision threshold selected. Several experiment results have shown that: when the decision threshold is too low, it will cause much more false alarm; when the decision threshold is too high, it will bring many missing detection. Therefore, it is crucial that choosing an optimal decision threshold according to the length of observation time. In this paper, the closed-form solution of the minimum-cost decision threshold is deduced by using the methodology of mathematical derivation, and a new criterion about selecting an optimal decision threshold is also proposed. At last, the conclusion is proved by simulation.

scholarly journals Three-Event Energy Detection with Adaptive Threshold for Spectrum Sensing in Cognitive Radio Systems

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3614 ◽  
Author(s):  
Alexandru Martian ◽  
Mahmood Jalal Ahmad Al Sammarraie ◽  
Călin Vlădeanu ◽  
Dimitrie C. Popescu
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Dynamic Spectrum Access ◽  
Energy Detection ◽  
Optimal Decision ◽  
Decision Threshold ◽  
Secondary Users ◽  
Adaptive Sensing ◽  
Decision Error ◽  
Radio Systems

Implementation of dynamic spectrum access (DSA) in cognitive radio (CR) systems requires the unlicensed secondary users (SU) to implement spectrum sensing to monitor the activity of the licensed primary users (PU). Energy detection (ED) is one of the most widely used methods for spectrum sensing in CR systems, and in this paper we present a novel ED algorithm with an adaptive sensing threshold. The three-event ED (3EED) algorithm for spectrum sensing is considered for which an accurate approximation of the optimal decision threshold that minimizes the decision error probability (DEP) is found using Newton’s method with forced convergence in one iteration. The proposed algorithm is analyzed and illustrated with numerical results obtained from simulations that closely match the theoretical results and show that it outperforms the conventional ED (CED) algorithm for spectrum sensing.

scholarly journals A Fast Detection Algorithm for the X-Ray Pulsar Signal

2017 ◽  
Vol 2017 ◽  
pp. 1-5 ◽  
Author(s):  
Hao Liang ◽  
Yafeng Zhan
Keyword(s):  
False Alarm ◽  
Navigation System ◽  
Detection Probability ◽  
Autonomous Navigation ◽  
Detection Algorithm ◽  
Observation Time ◽  
X Ray ◽  
Fast Detection ◽  
Simulation Results ◽  
Short Observation Time

The detection of the X-ray pulsar signal is important for the autonomous navigation system using X-ray pulsars. In the condition of short observation time and limited number of photons for detection, the noise does not obey the Gaussian distribution. This fact has been little considered extant. In this paper, the model of the X-ray pulsar signal is rebuilt as the nonhomogeneous Poisson distribution and, in the condition of a fixed false alarm rate, a fast detection algorithm based on maximizing the detection probability is proposed. Simulation results show the effectiveness of the proposed detection algorithm.

scholarly journals A Diffusion-Based Distributed Collaborative Energy Detection Algorithm for Spectrum Sensing in Cognitive Radio

2013 ◽  
Vol 05 (03) ◽  
pp. 276-279
Author(s):  
Junfang Li ◽  
Wenxiao Chen ◽  
Shaoli Kang ◽  
Yongming Guo
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Energy Detection ◽  
Detection Algorithm

An Effective Spectrum Sensing Method Based on Correlation Coefficient and Energy Detection

2014 ◽  
Vol 1023 ◽  
pp. 210-213
Author(s):  
Fu Lai Liu ◽  
Shou Ming Guo ◽  
Rui Yan Du
Keyword(s):  
Correlation Coefficient ◽  
Spectrum Sensing ◽  
Dynamic Spectrum Access ◽  
Energy Detection ◽  
Low Complexity ◽  
Noise Power ◽  
Decision Threshold ◽  
Test Statistic ◽  
Receiving Antenna ◽  
Influence Of Noise

Spectrum sensing is the key functionality for dynamic spectrum access in cognitive radio networks. Energy detection is one of the most popular spectrum sensing methods due to its low complexity and easy implementation. However, performance of the energy detector is susceptible to uncertainty in noise power. To overcome this problem, this paper proposes an effective spectrum sensing method based on correlation coefficient. The proposed method utilizes a single receiving antenna with a delay device to acquire the original received signal and the delayed signal. Then the correlation coefficient of the two signals is computed and the result is used as the test statistic. Theoretical analysis shows that the decision threshold is unrelated to noise power, thus the proposed approach can effectively overcome the influence of noise power uncertainty. Simulation results testify the effectiveness of the proposed method even in low signal-to-noise (SNR) conditions.

scholarly journals Statistical Properties of Energy Detection for Spectrum Sensing by Using Estimated Noise Variance

2019 ◽  
Vol 8 (2) ◽  
pp. 28 ◽  
Author(s):  
Xiao-Li Hu ◽  
Pin-Han Ho ◽  
Limei Peng
Keyword(s):  
False Alarm ◽  
Spectrum Sensing ◽  
False Alarm Probability ◽  
Energy Detection ◽  
Radio Spectrum ◽  
Statistical Properties ◽  
Constant False Alarm Rate ◽  
Noise Variance ◽  
Total Noise ◽  
Noise Receiver

In energy detection for cognitive radio spectrum sensing, the noise variance is usually assumed given, by which a threshold is set to guarantee a desired constant false alarm rate (CFAR) or a constant detection rate (CDR). However, in practical situations, the exact information of noise variance is generally unavailable to a certain extent due to the fact that the total noise consists of time-varying thermal noise, receiver noise, and environmental noise, etc. Hence, setting the thresholds by using an estimated noise variance may result in different false alarm probabilities from the desired ones. In this paper, we analyze the basic statistical properties of the false alarm probability by using estimated noise variance, and propose a method to obtain more suitable CFAR thresholds for energy detection. Specifically, we first come up with explicit descriptions on the expectations of the resultant probability, and then analyze the upper bounds of their variance. Based on these theoretical preparations, a new method for precisely obtaining the CFAR thresholds is proposed in order to assure that the expected false alarm probability can be as close to the predetermined as possible. All analytical results derived in this paper are testified by corresponding numerical experiments.

Performance measurement of one-bit hard decision fusion scheme for cooperative spectrum sensing in CR

2017 ◽  
Vol 8 (1) ◽  
pp. 9-16
Author(s):  
M. Al-Rawi
Keyword(s):  
False Alarm ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Additive White Gaussian Noise ◽  
False Alarm Probability ◽  
Energy Detection ◽  
Decision Fusion ◽  
Probability Effect ◽  
Probability Number ◽  
Hard Decision

This paper measures the performance of cooperative spectrum sensing, over Rayleigh-fading channel and additive white Gaussian noise, based on one-bit hard decision scheme for both AND and OR rules. Three measures based on energy detection are considered including effect of false alarm probability, effect of number of users, and effect of number of samples. Simulation results show that the detection probability increases with increasing false alarm probability, number of users, and number of samples for both AND and OR rules. Also, the performance of OR rule is better than the performance of AND rule.

An Algorithm Based on Double-Threshold Energy Detection in Cognitive Radio

2014 ◽  
Vol 643 ◽  
pp. 105-110
Author(s):  
Yuan Li ◽  
Jia Yin Chen ◽  
Xiao Feng Liu ◽  
Ming Chuan Yang
Keyword(s):  
Cognitive Radio ◽  
False Alarm ◽  
Spectrum Sensing ◽  
Mathematical Proof ◽  
Threshold Energy ◽  
Energy Detection ◽  
Probability Of Detection ◽  
Threshold Detection ◽  
Probability Of False Alarm ◽  
Double Threshold

Aiming at the situation where the double-threshold detection has been widely used without complete mathematical proof and condition of application, this paper proves its correctness under the circumstance of spectrum sensing, and circulates the condition where this method can work. The proof and simulation show that, comparing with traditional energy detection, this method can increase the probability of detection by 27% to 42% at most when the SNR is between-15dB and-2dB, while the probability of false alarm is increased by less than 2%.

scholarly journals Cooperative Spectrum Sensing Algorithm to Overcome Noise Fluctuations Based on Energy Detection in Sensing Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Guicai Yu ◽  
Han Wang ◽  
Wencai Du
Keyword(s):  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Signal To Noise Ratio ◽  
Average Power ◽  
Energy Detection ◽  
Detection Algorithm ◽  
Detection Sensitivity ◽  
Power Fluctuation ◽  
Sensing Systems ◽  
Noisy Signals

In sensing systems, nodes must be able to rapidly detect whether a signal from a primary transmitter is present in a certain spectrum. However, traditional energy-detection algorithms are poorly adapted to treating noisy signals. In this paper, we investigate how rapid energy detection and detection sensitivity are related to detection duration and average power fluctuation in noise. The results indicate that detection performance and detection sensitivity decrease quickly with increasing average power fluctuation in noise and are worse in situations with low signal-to-noise ratio. First, we present a dynamic threshold algorithm based on energy detection to suppress the influence of noise fluctuation and improve the sensing sensitivity. Then, we present a new energy-detection algorithm based on cooperation between nodes. Simulations show that the proposed scheme improves the resistance to average power fluctuation in noise for short detection timescales and provides sensitive detection that improves with increasing numbers of cooperative detectors. In other words, the proposed scheme enhances the ability to overcome noise and improves spectrum sensing performance.

scholarly journals Review on The Performance of Softened Two-Bit Hard Combination Scheme for Cooperative Spectrum Sensing

2018 ◽  
Vol 15 (1) ◽  
pp. 51-54
Author(s):  
Mohanad Abdulhamid
Keyword(s):  
False Alarm ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Signal To Noise Ratio ◽  
Additive White Gaussian Noise ◽  
False Alarm Probability ◽  
Energy Detection ◽  
Combination Scheme ◽  
Two Measures ◽  
Probability Number

Abstract This paper measures the performance of cooperative spectrum sensing, over Rayleigh fading channel and additive white Gaussian noise, based on softened two-bit hard combination scheme. Two measures based on energy detection are considered including effect of false alarm probability, and effect of number of users. Simulation results show that the detection probability increases with the increase of false alarm probability, number of users, and signal-to-noise-ratio.

A Dynamic Threshold Optimization Algorithm for Spectrum Sensing with Energy Detection in Cognitive Radio

2012 ◽  
Vol 236-237 ◽  
pp. 917-922
Author(s):  
Wei Ran Wang ◽  
Shu Bin Wang ◽  
Xin Yan Zhao
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Optimization Algorithm ◽  
Signal To Noise Ratio ◽  
Energy Detection ◽  
Detection Algorithm ◽  
Probability Of Detection ◽  
Dynamic Threshold ◽  
Threshold Optimization ◽  
Sensing Performance

In order to improve an efficiency of energy detection for a spectrum sensing in cognitive radio (CR), this paper proposes a dynamic threshold optimization algorithm. The traditional energy detection algorithm uses a fixed threshold, and can't guarantee always the optimal sensing performance in any environment. The improvement for sensing performance need to minimize the undetected probability and the probability of false alarm, and it is dissimilar for different CR users to accept these two errors. We improve the traditional energy detection algorithm, and firstly introduce a preference factor to characterize CR users’ different requirements for these two errors, then, propose a dynamic threshold optimization algorithm by minimizing integrated detection error for different signal-to-noise ratio (SNR). The simulation results show that the proposed algorithm effectively reduces the integrated spectrum sensing error, and increases the probability of detection, especially in low SNR.

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