Noise Uncertainty Effect on a Modified Two-Stage Spectrum Sensing Technique

2016 ◽  
Vol 1 (2) ◽  
pp. 341 ◽  
Author(s):  
Heba A.Tag El-Dien ◽  
Rokaia M. Zaki ◽  
Mohsen M. Tantawy ◽  
Hala M. Abdel-Kader
Keyword(s):  
Spectrum Sensing ◽  
Energy Detection ◽  
Primary User ◽  
Probability Of Detection ◽  
Minimum Eigenvalue ◽  
Two Stage ◽  
Noise Uncertainty ◽  
Second Stage ◽  
Single Detector ◽  
Maximum Minimum

Detecting the presence or absence of primary user is the key task of cognitive radio networks. However, relying on single detector reduces the probability of detection and increases the probability of missed detection. Combining two conventional spectrum sensing techniques by integrating their individual features improves the probability of detection especially under noise uncertainty. This paper introduces a modified two-stage detection technique that depends on the energy detection as a first stage due to its ease and speed of detection, and the proposed Modified Combinational Maximum-Minimum Eigenvalue based detection as a second stage under noise uncertainty and comperes it with the case of using Maximum-Minimum Eigenvalue and  Combinational Maximum-Minimum Eigenvalue as a second stage.

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.

An Adaptive Spectrum-Sensing Algorithm for Cognitive Radio Networks based on the Sample Covariance Matrix

2017 ◽  
Vol 67 (3) ◽  
pp. 325 ◽  
Author(s):  
Chhagan Charan ◽  
Rajoo Pandey
Keyword(s):  
Covariance Matrix ◽  
Spectrum Sensing ◽  
Primary User ◽  
Adaptive Threshold ◽  
Probability Of Detection ◽  
Superior Performance ◽  
Probability Of Error ◽  
Noise Uncertainty ◽  
Low Snr ◽  
Sample Covariance

<p>A novel adaptive threshold spectrum sensing technique based on the covariance matrix of received signal samples is proposed. The adaptive threshold in terms of signal to noise ratio (SNR) and spectrum utilisation ratio of primary user is derived. It considers both the probability of detection and the probability false alarm to minimise the overall decision error probability. The energy- based spectrum sensing scheme shows high vulnerability under noise uncertainty and low SNR. The existing covariance-based spectrum sensing technique overcomes the noise uncertainty problem but its performance deteriorates under low SNR. The proposed covariance-based scheme effectively addresses the low SNR problem. The superior performance of this scheme over the existing covariance-based detection method is confirmed by the simulation results in terms of probability of detection, probability of error, and requirement of samples for reliable detection of spectrum.</p>

Improved Two-Stage Spectrum Sensing for Cognitive Radio Networks

2019 ◽  
Vol 23 (6) ◽  
pp. 1052-1062
Author(s):  
Fidel Wasonga ◽  
Thomas O. Olwal ◽  
Adnan Abu-Mahfouz ◽  
◽  
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Feature Detection ◽  
Energy Detection ◽  
Probability Of Detection ◽  
Detection Accuracy ◽  
Two Stage ◽  
Probability Of Error ◽  
Average Spectrum ◽  
Sensing Time

Cognitive radio employs an opportunistic spectrum access approach to ensure efficient utilization of the available spectrum by secondary users (SUs). To allow SUs to access the spectrum opportunistically, the spectrum sensing process must be fast and accurate to avoid possible interference with the primary users. Previously, two-stage spectrum sensing methods were proposed that consider the sensing time and sensing accuracy parameters independently at the cost of a non-optimal spectrum sensing performance. To resolve this non-optimality issue, we consider both parameters in the design of our spectrum sensing scheme. In our scheme, we first derive optimal thresholds using an optimization equation with an objective function of maximizing the probability of detection, subject to the minimal probability of error. We then minimize the average spectrum sensing time using signal-to-noise ratio estimation. Our simulation results show that the proposed improved two-stage spectrum sensing (ITSS) scheme provides a 4%, 7%, and 6% better probability of detection accuracy rate than two-stage combinations of energy detection (ED) and maximum eigenvalue detection, energy detection and cyclostationary feature detection (CFD), and ED and combination of maximum-minimum eigenvalue (CMME) detection, respectively. The ITSS is superior also to single-stage ED by 19% and shows an improved average spectrum sensing time.

Adaptive Two-Stage Sensing Based on Energy Detection and Cyclostationary Feature Detection for Cognitive Radio Systems

2013 ◽  
Vol 411-414 ◽  
pp. 1521-1528 ◽  
Author(s):  
Yu Yang ◽  
Yan Li Ji ◽  
Han Hui Li ◽  
Du Lei ◽  
Meng Rui
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Feature Detection ◽  
Energy Detection ◽  
Probability Of Detection ◽  
Two Stage ◽  
Probability Of False Alarm ◽  
Detection Model ◽  
Radio Systems ◽  
Cyclostationary Feature Detection

In this paper, we investigate the features of energy detection and cyclostationary feature detection for spectrum sensing. In order to combine their advantages, we propose an adaptive two-stage sensing scheme which performs spectrum sensing using an energy detector first in cognitive radio networks. Then in the second stage, this scheme decides whether or not to implement cyclostationary feature detection based on the sensing results of the first stage. On the premise of meeting a given constraint on the probability of false alarm, the goal of our proposed scheme is to optimize the probability of detection and sensing speed at the same time. In order to obtain the optimal detection thresholds, we can formulate the detection model as a nonlinear optimization problem. Furthermore, the simulation results show that the proposed scheme improves the performance of spectrum sensing compared with the ones where only energy detection or cyclostationary feature detection is performed.

scholarly journals Implementation of Selected Spectrum Sensing Systems for Cognitive Radio Networks using FPGA Platform

2018 ◽  
Vol 8 ◽  
pp. 81-87 ◽  
Author(s):  
Hikmat N. Abdullah ◽  
Hadeel S. Abed
Keyword(s):  
Energy Consumption ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Primary User ◽  
Probability Of Detection ◽  
Second Stage ◽  
Sensing Systems ◽  
Functional Blocks ◽  
Reduce Energy Consumption ◽  
Two Stages

The energy efficient spectrum sensing method is very important in cognitive radio (CR), since high power drain may limit its implementation in mobile applications. The spectrum sensing feature consumes more energy than other functional blocks, as it depends on continuous detection of the presence or absence of the primary user (PU). In this paper, we proposed two methods to reduce energy consumption of the spectrum sensing feature. The first is of a single stage variety with a reduced number of sensed samples. The other uses two stages. The first stage performs coarse sensing for many subchannels, and the best subchannel is forwarded for fine sensing in the second stage. The performance of the proposed methods is evaluated in AWGN channel and compared with the existing approach. The proposed methods are simulated using Matlab and ModelSim and are then hardware implemented using the Altera Cyclone II FPGA board. Simulation results show that the proposed methods offer an improvement in energy consumption with an acceptable reduction in the probability of detection. At Eb/N0 Eb/N0 Eb/N0 of 0 dB, the energy consumption is reduced by 50% and 72% in the first and second proposed method, respectively, compared to the traditional method (100% sensing).

A Modified Energy Detection Algorithm Based on Primary User Activity for Cognitive Radio Networks

2014 ◽  
Vol 548-549 ◽  
pp. 1351-1354
Author(s):  
Gang Tao Han ◽  
Ying Qiang Ding ◽  
Xiao Min Mu ◽  
Jian Kang Zhang
Keyword(s):  
Spectrum Sensing ◽  
Dynamic Spectrum Access ◽  
Energy Detection ◽  
Primary User ◽  
Detection Algorithm ◽  
Probability Of Detection ◽  
Spectrum Access ◽  
Theory Analysis ◽  
Channel State ◽  
User Activity

Spectrum sensing is used to identify the unused frequency bands and as such plays a key role in dynamic spectrum access. In most of the existing spectrum sensing models, the channel state of primary user is assumed unchanged within the spectrum sensing duration, which is not suitable for the channels with high activity, in which the primary user accesses or vacates from the channel frequently. In this paper, a Modified Energy Detection (MED) algorithm is proposed for this scenarios by considering the primary user activity within the spectrum sensing duration. Theory analysis and computer simulation results show that both the probability of detection and false alarm in this scenarios have been improved with our MED.

Two-Stage Spectrum Sensing for Cognitive Radio Using Eigenvalues Detection

2020 ◽  
Vol 12 (4) ◽  
pp. 18-36
Author(s):  
Faten Mashta ◽  
Wissam Altabban ◽  
Mohieddin Wainakh
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Primary User ◽  
Detection Performance ◽  
Probability Of Detection ◽  
Energy Detector ◽  
Detection Methods ◽  
Two Stage ◽  
Low Snr ◽  
Good Detection

Spectrum sensing in cognitive radio has difficult and complex requirements, requiring speed and good detection performance at low SNR ratios. As suggested in IEEE 802.22, the primary user signal needs to be detected at SNR = -21dB with a probability of detection exceeds 0.9. Conventional spectrum sensing methods such as the energy detector, which is characterized by simplicity with good detection performance at high SNR values, are ineffective at low SNR values, whereas eigenvalues detection methods have good detection performance at low SNR ratios, but they have high complexity. In this paper, the authors investigate the process of spectrum sensing in two stages: in the first stage (coarse sensing), the energy detector is adopted, while in the second stage (fine sensing), eigenvalues detection methods are used. This method improves performance in terms of probability of detection and computational complexity, as the authors compared the performance of two-stage sensing scheme with ones where only energy detection or eigenvalues detection is performed.

Energy Detection Spectrum Sensing with Discontinuous Primary User Signal

2009 ◽  
Author(s):  
F. Penna ◽  
C. Pastrone ◽  
M. A. Spirito ◽  
R. Garello
Keyword(s):  
Spectrum Sensing ◽  
Energy Detection ◽  
Primary User

Cross-Layer Performance Analysis of the Unreliable Data Transmission for Decentralized Cognitive MAC Protocol under Multiple Secondary Users Scenario

2013 ◽  
Vol 1 (1) ◽  
pp. 74-85
Author(s):  
Xiaofeng Hu ◽  
Xianzhong Xie ◽  
Ting Song
Keyword(s):  
Data Transmission ◽  
Mac Protocol ◽  
Energy Detection ◽  
Primary User ◽  
Sampling Time ◽  
Probability Of Detection ◽  
Cross Layer ◽  
Secondary Users ◽  
Target Probability ◽  
A Minor

AbstractThe effect of multiple secondary users detecting the same primary user channel during a minor period on the performance of traditional energy detection is investigated. In order to achieve the target probability of detection, the minimum sampling time (MST) for energy detection is derived under the limitation of energy detection (LED), when the random arrival of the secondary users is taken into account. Jointly considering both spectrum sensing and access, we derive the probability of unreliable data transmission for decentralized cognitive MAC (DC-MAC) protocol based on MST under LED. The numerical results show that the simulation and theoretical analysis match very well. The reliability of data transmission is significantly degraded by the secondary users’ traffic. With the target probability of detection increasing, the reliable throughput reduces.

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