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.

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.

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.

scholarly journals Compressive cyclostationary spectrum sensing with a constant false alarm rate

2017 ◽  
Vol 2017 (1) ◽  
Author(s):  
Andreas Bollig ◽  
Anastasia Lavrenko ◽  
Martijn Arts ◽  
Rudolf Mathar
Keyword(s):  
False Alarm ◽  
False Alarm Rate ◽  
Spectrum Sensing ◽  
Constant False Alarm Rate

scholarly journals A Novel Sensing Strategy Based on Energy Detector for Spectrum Sensing

2019 ◽  
Vol 9 (21) ◽  
pp. 4634 ◽  
Author(s):  
Hai Huang ◽  
Jia Zhu ◽  
Junsheng Mu
Keyword(s):  
False Alarm ◽  
Spectrum Sensing ◽  
Detection Probability ◽  
False Alarm Probability ◽  
Energy Detector ◽  
Accuracy Improvement ◽  
Classical Scheme ◽  
Sensing Performance

Sensing strategy directly influences the sensing accuracy of a spectrum sensing scheme. As a result, the optimization of a sensing strategy appears to be of great significance for accuracy improvement in spectrum sensing. Motivated by this, a novel sensing strategy is proposed in this paper, where an improved tradeoff among detection probability, false-alarm probability and available throughput is obtained based on the energy detector. We provide the optimal sensing performance and exhibit its superiority in theory compared with the classical scheme. Finally, simulations validate the conclusions drawn in this paper.

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.

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 Analysis of Cognitive Radio Spectrum Sensing Techniques over Nakagami-m Fading Channel

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Fading Channel ◽  
Feature Detection ◽  
Energy Detection ◽  
Radio Spectrum ◽  
Awgn Channel ◽  
Novel Approach ◽  
Spectrum Scarcity ◽  
Cyclostationary Feature Detection

As the demand of wireless communication increases exponentially, with the same ratio scarcity of spectrum also originates. To overcome this spectrum scarcity a novel approach, Cognitive Radio (CR) shows development of an opportunistic and promising technology. This paper explores implementation and analysis of the CR spectrum sensing techniques such as Matched filtering, Energy detection and Cyclostationary feature detection on MATLAB platform by simulation. We analyze performance of these techniques over, Nakagami-m fading channel with AWGN channel for both the BPSK and QPSK modulation.

Analysis of Spectrum Sensing in Cognitive Radio Network with OFDM

2018 ◽  
Vol 8 (6) ◽  
pp. 84
Author(s):  
Shadab Ahmed Khan ◽  
Pawandeep Kaur
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Energy Detection ◽  
Radio Spectrum ◽  
Probability Of Detection ◽  
Spectrum Utilization ◽  
Wireless Applications ◽  
Novel Technology ◽  
Cognitive Environment

With the development of a new and ever expanding wireless applications and services, spectrum resources are facing in demands. In present scenario, the spectrum allotment has been done by providing each new service with its own fixed frequency Slot. Most of the user’s spectrum is already assigned, so it becomes very difficult to find spectrum for other users or existing users. This leads to the scarcity of available spectrum and inefficient channel utilization. Cognitive radio is a novel technology which improves the spectrum utilization by allowing secondary user to borrow unused radio spectrum from primary licensed users or to share the spectrum with the primary users. Present paper deals with the spectrum sensing in which multiple users detect the spectrum gap through energy detection and investigate the detection performance in an efficient and implementable way. Simulation results showed that the probability of detection is achieved at small value SNR in case of OFDM modulation as compare the other and simple cognitive environment.

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