False Alarm Probability of the Spectrum Sensing Scheme Using the Maximum of Power Spectrum

Author(s):  
Chang Heon Lim
2019 ◽  
Vol 8 (2) ◽  
pp. 28 ◽  
Author(s):  
Xiao-Li Hu ◽  
Pin-Han Ho ◽  
Limei Peng

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.


2019 ◽  
Vol 9 (21) ◽  
pp. 4634 ◽  
Author(s):  
Hai Huang ◽  
Jia Zhu ◽  
Junsheng Mu

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.


2017 ◽  
Vol 8 (1) ◽  
pp. 9-16
Author(s):  
M. Al-Rawi

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.


2018 ◽  
Vol 15 (1) ◽  
pp. 51-54
Author(s):  
Mohanad Abdulhamid

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.


2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Daniele Borio ◽  
Emanuele Angiuli ◽  
Raimondo Giuliani ◽  
Gianmarco Baldini

Spectrum Sensing (SS) is an important function in Cognitive Radio (CR) to detect primary users. The design of SS algorithms is one of the most challenging tasks in CR and requires innovative hardware and software solutions to enhance detection probability and minimize low false alarm probability. Although several SS algorithms have been developed in the specialized literature, limited work has been done to practically demonstrate the feasibility of this function on platforms with significant computational and hardware constraints. In this paper, SS is demonstrated using a low cost TV tuner as agile front-end for sensing a large portion of the Ultra-High Frequency (UHF) spectrum. The problems encountered and the limitations imposed by the front-end are analysed along with the solutions adopted. Finally, the spectrum sensor developed is implemented on an Android device and SS implementation is demonstrated using a smartphone.


2013 ◽  
Vol 765-767 ◽  
pp. 2305-2308
Author(s):  
Shou Tao Lv ◽  
Ze Yang Dai ◽  
Jian Liu

In this paper, we propose a reliable spectrum sensing strategy based on multiple-antenna technique, called RSS-MAT, to combat the channel uncertainties. We derive the closed-form expressions of the false alarm probability and detection probability for RSS-MAT. Finally, we present simulation results to validate our performance analysis. As expected, the simulation results show that RSS-MAT outperforms the spectrum sensing strategy with single antenna.


2021 ◽  
Author(s):  
Rania A. Mokhtar ◽  
Rashid Saeed ◽  
Hesham Alhumyani

Abstract Cognitive radio (CR) is one of the most promising technology soon due to the scarcity of the spectrum, especially at microwave band. CR faces massive resistance from the industry because of the potential interference caused by the secondary users. Spectrum sensing forms an important functionality for CR systems. However, such detection performance is usually compromised by shadowing and fading channel conditions. Cooperative sensing is one of the crucial solutions to overcome degraded detection performance. To improve the sensing performance and reduce the reporting error, a distributed architecture for processing and fusion of sensing information is proposed in this work. In dense network scenarios, the decision fusion for cooperated users could be complex and reported sensing traffic may require large bandwidth. This paper proposes a new distributed detection and adapted threshold based on controlled false alarm probability to improve sensing reliability and efficiency in a highly Rayleigh faded environment. A distributed detection is developed by selecting fusion nodes (FN) that are dynamically selected from a group of nodes. The detection threshold is calculated adaptively using the link quality indicator (LQI) of the sensing channel. Moreover, the proposed method can significantly minimize the typically transmitted bits in the reporting channel. The paper also discussed in detail the design parameter of the CR number on the performance of fusion values. The simulation analysis shows that the performance of the distributed cooperative sensing (DCS) process is considerably improved by the adapted threshold. The numerical results demonstrated that the error was remarkably minimized. The ROC curve of the sensing process is notably improved for detection probability and false alarm probability, respectively. Finally, it was shown that the requirement of sensitivity can be greatly improved up to 0.95.


Author(s):  
Durga R ◽  
Selvaraj D

Spectrum sensing techniques are used for aquising the frequency spectrum in cognitive radio. From research, the efficiency of the spectrum sensing technique increases only if its complexity is increased and if its complexity is decreased then its efficiency decreases. so, a new technique is proposed in this paper based on Dispersion Detection (DD) to balance both complexity and efficiency. Using this detection technique, the false alarm probability is derived for multiple antenna using test statistic distribution. The decision threshold is derived to provide the accurate results. The derived values are verified with Monto Carlo simulation.


2013 ◽  
Vol 380-384 ◽  
pp. 1499-1504
Author(s):  
Shi Ding Zhang ◽  
Hai Lian Wang ◽  
Jing Ping Mei

Cooperative spectrum sensing is a key technology to tackle the challenges such as fading or hidden terminal problem in local spectrum sensing of cognitive radio system. Conventional cooperative method can improve the detection performance in some sense, but increase overhead of control channel. In order to reduce the overhead, a new cooperative spectrum sensing algorithm based on confidence level is proposed. In this algorithm, the maximum-eigenvalue-based detection scheme is carried out to obtain the local spectrum detection and the detection probability and false alarm probability of each secondary user are used to estimate the reliability of the sensing decision. The test statistic of the secondary users with high reliability are chosen and sent to fusion center. Then weighted factors of chosen secondary users are derived from creditability values, and the global decision is made by weighted fusion at fusion center. The simulation results show that the proposed algorithm improves the detection probability in the guarantee of the false-alarm probability close to 0 and saves half of the overhead in the control channel.


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