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.

Robust Performance of Spectrum Sensing in Cognitive Radio Networks

2012 ◽  
pp. 43-59
Author(s):  
Shimin Gong ◽  
Ping Wang ◽  
Jianwei Huang
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Detection Probability ◽  
Optimal Decision ◽  
Decision Threshold ◽  
Performance Bounds ◽  
Secondary Users ◽  
Cognitive Radio Systems ◽  
Single User ◽  
Radio Systems

Harmonic coexistence of cognitive radio systems and licensed systems requires the secondary users to have the capability of sensing and keeping track of primary users’ transmissions. While existing spectrum sensing methods usually assume known distributions of the primary signals, such an assumption is often not true in practice. As a result, applying existing sensing methods will often lead to unreliable detection performance in practical networks. In this chapter, the authors try to investigate the sensing performance under the distribution uncertainty of primary signals. They first investigate the performance bounds for single user detection with unknown distribution, and provide an analytical expression for the lower bound of detection probability. Moreover, they bring the distribution uncertainty into multi-user cooperative sensing. The authors formulate the optimal sensing design as a robust optimization problem, and propose an iterative algorithm to determine the optimal decision threshold for each user. Extensive simulations demonstrate the effectiveness of the proposed algorithm.

scholarly journals Spectrum Sensing in Cognitive Radio using Frequency Domain

2019 ◽  
Vol 9 (2) ◽  
pp. 3475-3477
Keyword(s):  
Cognitive Radio ◽  
Frequency Domain ◽  
Spectrum Sensing ◽  
Bandwidth Allocation ◽  
Dynamic Spectrum Access ◽  
Signal To Noise Ratio ◽  
Wide Band ◽  
Energy Detection ◽  
Secondary Users ◽  
Sensing Applications

An efficient bandwidth allocation and dynamic bandwidth access away from its previous limits is referred as cognitive radio (CR).The limited spectrum with inefficient usage requires the advances of dynamic spectrum access approach, where the secondary users are authorized to utilize the unused temporary licensed spectrum. For this reason it is essential to analyze the absence/presence of primary users for spectrum usage. So spectrum sensing is the main requirement and developed to sense the absence/ presence of a licensed user. This paper shows the design model of energy detection based spectrum sensing in frequency domain utilizing Binary Symmetric Channel (BSC) ,Additive white real Gaussian channel (AWGN), Rayleigh fading channel users for 16-Quadrature Amplitude Modulation(QAM) which is utilized for the wide band sensing applications at low Signal to noise Ratio(SNR) level to reduce the false error identification. The spectrum sensing techniques has least computational complexity. Simulink model for the energy detection based spectrum sensing using frequency domain in MATLAB 2014a.

scholarly journals Analysis of the Impact of Detection Threshold Adjustments and Noise Uncertainty on Energy Detection Performance in MIMO-OFDM Cognitive Radio Systems

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 631
Author(s):  
Josip Lorincz ◽  
Ivana Ramljak ◽  
Dinko Begušić
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Detection Method ◽  
Detection Threshold ◽  
Energy Detection ◽  
Primary User ◽  
Noise Uncertainty ◽  
Cognitive Radio Systems ◽  
Radio Systems ◽  
The Impact

Due to the capability of the effective usage of the radio frequency spectrum, a concept known as cognitive radio has undergone a broad exploitation in real implementations. Spectrum sensing as a core function of the cognitive radio enables secondary users to monitor the frequency band of primary users and its exploitation in periods of availability. In this work, the efficiency of spectrum sensing performed with the energy detection method realized through the square-law combining of the received signals at secondary users has been analyzed. Performance evaluation of the energy detection method was done for the wireless system in which signal transmission is based on Multiple-Input Multiple-Output—Orthogonal Frequency Division Multiplexing. Although such transmission brings different advantages to wireless communication systems, the impact of noise variations known as noise uncertainty and the inability of selecting an optimal signal level threshold for deciding upon the presence of the primary user signal can compromise the sensing precision of the energy detection method. Since the energy detection may be enhanced by dynamic detection threshold adjustments, this manuscript analyses the influence of detection threshold adjustments and noise uncertainty on the performance of the energy detection spectrum sensing method in single-cell cognitive radio systems. For the evaluation of an energy detection method based on the square-law combining technique, the mathematical expressions of the main performance parameters used for the assessment of spectrum sensing efficiency have been derived. The developed expressions were further assessed by executing the algorithm that enabled the simulation of the energy detection method based on the square-law combining technique in Multiple-Input Multiple-Output—Orthogonal Frequency Division Multiplexing cognitive radio systems. The obtained simulation results provide insights into how different levels of detection threshold adjustments and noise uncertainty affect the probability of detection of primary user signals. It is shown that higher signal-to-noise-ratios, the transmitting powers of primary user, the number of primary user transmitting and the secondary user receiving antennas, the number of sampling points and the false alarm probabilities improve detection probability. The presented analyses establish the basis for understanding the energy detection operation through the possibility of exploiting the different combinations of operating parameters which can contribute to the improvement of spectrum sensing efficiency of the energy detection method.

scholarly journals 5G cognitive radio system design with new algorithm asynchronous spectrum sensing

2021 ◽  
Vol 10 (4) ◽  
pp. 2046-2054
Author(s):  
Mohammed Mehdi Saleh ◽  
Ahmed A. Abbas ◽  
Ahmed Hammoodi
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Energy Detection ◽  
Primary User ◽  
Spectrum Access ◽  
Secondary Users ◽  
Radio System ◽  
Wireless Applications ◽  
Fifth Generation ◽  
Time Required

Due to the rapid increase in wireless applications and the number of users, spectrum scarcity, energy consumption and latency issues will emerge, notably in the fifth generation (5G) system. Cognitive radio (CR) has emerged as the primary technology to address these challenges, allowing opportunist spectrum access as well as the ability to analyze, observe, and learn how to respond to environmental 5G conditions. The CR has the ability to sense the spectrum and detect empty bands in order to use underutilized frequency bands without causing unwanted interference with legacy networks. In this paper, we presented a spectrum sensing algorithm based on energy detection that allows secondary user SU to transmit asynchronously with primary user PU without causing harmful interference. This algorithm reduced the sensing time required to scan the whole frequency band by dividing it into n sub-bands that are all scanned at the same time. Also, this algorithm allows cognitive radio networks (CRN) nodes to select their operating band without requiring cooperation with licensed users. According to the BER, secondary users have better performance compared with primary users.

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.

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.

Energy Detection Approach for Spectrum Sensing in Cognitive Radio Systems with the Use of Random Sampling

2014 ◽  
Vol 79 (2) ◽  
pp. 1053-1061 ◽  
Author(s):  
Hayat Semlali ◽  
Najib Boumaaz ◽  
Abdallah Soulmani ◽  
Abdelilah Ghammaz ◽  
Jean-François Diouris
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Random Sampling ◽  
Energy Detection ◽  
Detection Approach ◽  
Cognitive Radio Systems ◽  
Radio Systems

scholarly journals An Optimized and Trained Model of Cooperative Sensing for Cognitive Radio Networks

2019 ◽  
Vol 8 (3) ◽  
pp. 5176-5182
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Search Algorithm ◽  
Decision Threshold ◽  
Secondary Users ◽  
Communication Problems ◽  
Local Decision ◽  
Huge Impact ◽  
Radio Technology

Sensing based spectrum allocation is one of the solutions to bridge the gap between spectrum scarcity and underutilization of allocated spectrum. In this context, cognitive radio technology has become the prominent solution for future wireless communication problems. To accurately detect the spectrum availability, CRN uses cooperative spectrum sensing where N number of selected nodes will be involved in making a decision on spectrum occupation. Various sensing parameters such as sensing duration (τ), decision threshold (λ), number of nodes (N) and decision rule (K) have huge impact on the performance of cooperative spectrum sensing. In addition, there are constraints on energy consumption and protection of licensed user’s needs to be considered. Our work focuses on optimization of sensing parameters to maximize the throughput of the cognitive radio network maintaining the energy efficiency and protecting the licensed users from the interference caused by the secondary users. The proposed work uses convex optimization to optimize sensing duration and two-dimensional search algorithm to find the values N and K. Further optimization is done by comparing local decision with cooperative decision.

Research on Dynamic Threshold Based Energy Detection in Cognitive Radio Systems

2012 ◽  
Vol 462 ◽  
pp. 506-511 ◽  
Author(s):  
Gui Cai Yu ◽  
Cheng Zhi Long ◽  
Man Tian Xiang
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Energy Detection ◽  
Detection Algorithm ◽  
Dynamic Threshold ◽  
Noise Power ◽  
Noise Uncertainty ◽  
Spectrum Detection ◽  
Radio Systems ◽  
Short Time

In cognitive radio networks, nodes should have the capability to decide whether a signal from a primary transmitter is locally present or not in a certain spectrum within a short detection period. Traditional spectrum sensing schemes based on fixed threshold are sensitive to noise uncertainty, a fractional fluctuate of average noise power in a short time can lead the performance of spectrum detection drop seriously. This paper presents a new spectrum detection algorithm based on dynamic threshold. Theoretical results show that the proposed scheme debate the noise uncertainty, and good detection performance can be gained, if suitable dynamic threshold is chosen. In other words, the proposed scheme can enhance the robustness against noise and improve the capacity of spectrum sensing.

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