Hybrid Cooperative Energy Detection Techniques in Cognitive Radio Networks

2015 ◽  
pp. 1-37 ◽  
Author(s):  
Raza Umar ◽  
Fahham Mohammed ◽  
Mohamed Deriche ◽  
Asrar U. H. Sheikh
Keyword(s):  
Cognitive Radio ◽  
A Priori ◽  
Energy Detection ◽  
Communication Overhead ◽  
Test Statistic ◽  
Local Data ◽  
Secondary Users ◽  
Detection Techniques ◽  
Depth Analysis ◽  
Significant Performance

Cognitive Radio (CR) has emerged as a smart solution to spectrum bottleneck faced by current wireless services under which licensed spectrum is made available to unlicensed Secondary Users (SUs) through robust and efficient Spectrum Sensing (SS). Energy Detection (ED) is the dominantly used SS approach owing to its low computational complexity and ability to identify spectrum holes without requiring a priori knowledge of primary transmission characteristics. In this chapter, the authors present an in-depth analysis of the ED test statistic. Based on the double threshold ED, they analyze the performance of a Hybrid PSO-OR (Particle Swarm Optimization and OR) algorithm for cooperative SS. The sensing decision of “fuzzy” SUs is optimized using PSO and the final collective decision is made based on OR rule. The idea of using two thresholds is introduced to reduce the communication overhead in reporting local data/decision to the fusion center, which also offers reduced energy consumption. The Hybrid PSO-OR algorithm is shown to exhibit significant performance gain over the Hybrid EGC-OR algorithm.

scholarly journals Performance of p-Norm Detector in Cognitive Radio Networks with Cooperative Spectrum Sensing in Presence of Malicious Users

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Nandita Lavanis ◽  
Devendra Jalihal
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Random Variable ◽  
Energy Detection ◽  
Primary User ◽  
Test Statistic ◽  
Secondary Users ◽  
Probability Of False Alarm ◽  
Standard Energy

A cognitive radio network (CRN) with a cooperative spectrum sensing scheme is considered. This CRN has a primary user and multiple secondary users, some of which are malicious secondary users (MSUs). Energy detection at each SU is performed using a p-norm detector with p≥2, where p=2 corresponds to the standard energy detector. The MSUs are capable of perpetrating spectrum sensing data falsification (SSDF) attacks. At the fusion center (FC), an algorithm is used to suppress these MSUs which could be either an adaptive weighing algorithm or one of the following: Tietjen-Moore (TM) test or Peirce’s criterion. This is followed by computation of a test statistic (TS) which is a random variable. In this paper, we assume TS to have either a Gamma or a Gaussian distribution and calculate the threshold accordingly. We provide closed-form expressions of probability of false alarm and probability of miss-detection under both assumptions. We show that Gaussian assumption of TS is more suited in presence of an SSDF attack when compared with the Gamma assumption. We also compare the detection performance for various values of p and show that p=3 along with the Gaussian assumption is the best amongst all the cases considered.

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 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.

scholarly journals An Efficient Contention-Window Based Reporting for Internet of Things Features in Cognitive Radio Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Muhammad Sajjad Khan ◽  
Junsu Kim ◽  
Eung Hyuk Lee ◽  
Su Min Kim
Keyword(s):  
Cognitive Radio ◽  
Internet Of Things ◽  
Evidence Theory ◽  
Radio Networks ◽  
Contention Window ◽  
Communication Overhead ◽  
Fusion Center ◽  
Bandwidth Utilization ◽  
Secondary Users ◽  
Reporting Scheme

Internet of things (IoT) is a new challenging paradigm for connecting heterogeneous networks. However, an explosive increase in the number of IoT cognitive users requires a mass of sensing reporting; thus, it increases complexity of the system. Moreover, bandwidth utilization, reporting time, and communication overhead arise. To realize spectrum sensing, how to collect sensing results by reducing the communication overhead and the reporting time is a problem of major concern in future wireless networks. On the other hand, cognitive radio is a promising technology to access the spectrum opportunistically. In this paper, we propose a contention-window based reporting approach with a sequential fusion mechanism. The proposed reporting scheme reduces the reporting time and the communication overhead by collecting sensing results from the secondary users with the highest reliability at a fusion center by utilizing Dempster-Shafer evidence theory. The fusion center broadcasts the sensing results once a global decision requirement is satisfied. Through simulations, we evaluate the proposed scheme in terms of percentage of the number of reporting secondary users, error probability, percentage of reporting, and spectral efficiency. As a result, it is shown that the proposed scheme is more effective than a conventional order-less sequential reporting scheme.

Interference Statistics and Capacity-Outage Analysis in Cognitive Radio Networks

2015 ◽  
pp. 711-744
Author(s):  
Mahsa Derakhshani ◽  
Tho Le-Ngoc
Keyword(s):  
Cognitive Radio ◽  
Fading Channels ◽  
Statistical Models ◽  
Primary User ◽  
Secondary Users ◽  
Detection Techniques ◽  
Outage Performance ◽  
Cooperative Detection ◽  
Aggregate Interference ◽  
Nakagami Fading Channels

This chapter presents a study on the interference caused by Secondary Users (SUs) due to miss-detection errors and its effects on the capacity-outage performance of the Primary User (PU) in a cognitive radio network assuming Rayleigh and Nakagami fading channels. The effect of beacon transmitter placement on aggregate interference distribution and capacity-outage performance is studied considering two scenarios of beacon transmitter placement: a beacon transmitter located at a PU transmitter or at a PU receiver. Based on the developed statistical models for the interference distribution, closed-form expressions for the capacity-outage probability of the PU are derived to examine the effects of various system parameters on the performance of the PU in the presence of interference from SUs. Furthermore, the model is extended to investigate the cooperative sensing effect on aggregate interference statistical model and capacity-outage performance considering OR (i.e., logical OR operation) and Maximum Likelihood (ML) cooperative detection techniques.

scholarly journals Enhanced Sensing and Sum-Rate Analysis in a Cognitive Radio-Based Internet of Things

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2525 ◽  
Author(s):  
Md. Sipon Miah ◽  
Kazi Mowdud Ahmed ◽  
Md. Khairul Islam ◽  
Md. Ashek Raihan Mahmud ◽  
Md. Mahbubur Rahman ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Internet Of Things ◽  
Spectrum Sensing ◽  
Energy Detection ◽  
Uncertain Environment ◽  
Detection Techniques ◽  
Leibler Divergence ◽  
Local Decision ◽  
Sum Rate ◽  
Sensing Performance

Spectrum sensing plays a vital role in cognitive radio networks (CRNs) for identifying the spectrum hole. However, an individual cognitive radio user in a CRN does not obtain sufficient sensing performance and sum rate of the primary and secondary links to support the future Internet of Things (IoT) using conventional detection techniques such as the energy detection (ED) technique in a noise-uncertain environment. In an environment comprising noise uncertainty, the performance of conventional energy detection techniques is significantly degraded owing to the noise fluctuation caused by the noise temperature, interference, and filtering. To mitigate this problem, we present a cooperative spectrum sensing technique that comprises the use of the Kullback–Leibler divergence (KLD) in cognitive radio-based IoT (CR-IoT). In the proposed method, each unlicensed IoT device that is capable of spectrum sensing, which is called a CR-IoT user, makes a local decision using the KLD technique. The spectrum sensing performed with the KLD requires a smaller number of samples than other conventional approaches, e.g., energy detection, for reliable sensing even in a noise uncertain environment. After the local decision is made, each CR-IoT user sends its own local decision result to the corresponding fusion center, which makes a global decision using the soft fusion rule. The results obtained through simulations show that the proposed KLD scheme achieves a better sensing performance, i.e., higher detection and lower false-alarm probabilities, enhances the sum rate, and reduces the total time as compared to the conventional ED scheme under various fading channels.

Review of Spectrum Sensing Techniques in Cognitive Radio Networks

2019 ◽  
pp. 85-107
Author(s):  
Ala Eldin Omer
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Feature Detection ◽  
Matched Filter ◽  
Internal State ◽  
Energy Detection ◽  
Detection Sensitivity ◽  
Detection Techniques ◽  
Radio Technology ◽  
Cyclostationary Feature Detection

Most frequency spectrum bands are licensed to certain services to avoid the interference between various networks, but the spectrum occupancy measurements show that few portions of this spectrum are fully efficiently used. Cognitive radio is a future radio technology that is aware of its environment, internal state, and can change its operating behavior (transmitter parameters) accordingly. Through this technology the unlicensed users can use the underutilized spectrum without causing any harmful interference to the licensed users. Its key domains are sensing, cognition, and adaptation. The spectrum sensing problem is one of the most challenging issues in cognitive radio systems to detect the available frequency bands. This chapter introduces the concepts of various transmitter detection techniques, namely energy detection, matched filter detection, and cyclostationary feature detection. The chapter also discusses other sensing techniques that are introduced to enhance the detection performance of the conventional energy detector. Additionally, the introduced sensing techniques are implemented using extensive MATLAB simulations and their performances are evaluated and compared in terms of sensing time, detection sensitivity, and ease of implementation. The implementation is based on BPSK and QPSK modulation schemes under various SNR values for AWGN noisy channel with Rayleigh fading.

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.

A QoS-Aware Power-Control Game Scheme for Secondary Users in Cognitive Radio Network

2012 ◽  
Vol 263-266 ◽  
pp. 1127-1133
Author(s):  
Xiang Yin Ran ◽  
Peng Bo Si ◽  
Yan Hua Zhang ◽  
Rui Zhe Yang
Keyword(s):  
Cognitive Radio ◽  
Power Control ◽  
Signal To Noise Ratio ◽  
Secondary Users ◽  
Significant Performance ◽  
Average Utility ◽  
Power Game ◽  
Cooperative Power ◽  
Game Scheme

To deal with the power control problem in cognitive radio (CR) networks, in this paper, the non-cooperative power game is studied, in which each CR user distributedly and asynchronously updates its transmission power. Taking into account the different quality of service (QoS) requirements, with the objective as maximizing the average utility of each CR user under the interference power constraints of primary users, we propose a QoS-aware power control game scheme and introduce the sigmoid efficiency function related with CR user’s signal-to-noise ratio threshold and the price function. Besides, extensive simulation results are presented to show the significant performance improvement of the proposed scheme compared to the existing ones.

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