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 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.

Deep Cooperative Spectrum Sensing Utilizing Recurrent Convolutional Neural Networks

2020 ◽  
Author(s):  
Rahil Sarikhani ◽  
Farshid Keynia
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Deep Learning ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Recurrent Neural Network ◽  
Cooperative Spectrum Sensing ◽  
Primary User ◽  
Secondary Users ◽  
Spectrum Holes

Abstract Cognitive Radio (CR) network was introduced as a promising approach in utilizing spectrum holes. Spectrum sensing is the first stage of this utilization which could be improved using cooperation, namely Cooperative Spectrum Sensing (CSS), where some Secondary Users (SUs) collaborate to detect the existence of the Primary User (PU). In this paper, to improve the accuracy of detection Deep Learning (DL) is used. In order to make it more practical, Recurrent Neural Network (RNN) is used since there are some memory in the channel and the state of the PUs in the network. Hence, the proposed RNN is compared with the Convolutional Neural Network (CNN), and it represents useful advantages to the contrast one, which is demonstrated by simulation.

Game Theory for Cognitive Radio Networks

Game Theory ◽  
2017 ◽  
pp. 487-502
Author(s):  
Sungwook Kim
Keyword(s):  
Cognitive Radio ◽  
Cognitive Abilities ◽  
Cognitive Radios ◽  
Primary User ◽  
Spectrum Management ◽  
Cognitive Networks ◽  
Wireless Devices ◽  
New Paradigm ◽  
Secondary Users ◽  
Dynamic Spectrum Management

A cognitive radio is an intelligent radio that can be programmed and configured dynamically. Its transceiver is designed to use the best wireless channels in its vicinity. Such a radio automatically detects available channels in the wireless spectrum, then accordingly changes its transmission or reception parameters to allow more concurrent wireless communications in a given spectrum band at one location. This process is a form of dynamic spectrum management. In recent years, the development of intelligent, adaptive wireless devices called cognitive radios, together with the introduction of secondary spectrum licensing, has led to a new paradigm in communications: cognitive networks. Cognitive networks are wireless networks that consist of several types of users: often a primary user and secondary users. These cognitive users employ their cognitive abilities to communicate without harming the primary users. The study of cognitive networks is relatively new and many questions are yet to be answered. This chapter furthers the study.

scholarly journals Outage Performance Improvement by Selected User in D2D Transmission and Implementation of Cognitive Radio-Assisted NOMA

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4840
Author(s):  
Dinh-Thuan Do ◽  
Minh-Sang Van Nguyen ◽  
Byung Moo Lee
Keyword(s):  
Cognitive Radio ◽  
Fading Channels ◽  
Interference Cancellation ◽  
Rayleigh Fading ◽  
Positive Impact ◽  
System Model ◽  
Outage Performance ◽  
Secondary Network ◽  
Asymptotic Expressions ◽  
D2d Transmission

In this paper, we investigate the outage performance in secondary network of cognitive radio (CR) employing non-orthogonal multiple access (NOMA) wireless networks over Rayleigh fading channels. The considered system model adopts device-to-device (D2D) transmission together with traditional communication to form a new system model, namely CR-D2DNOMA network. The specific user is selected from multiple D2D-Tx users (D2Ds) to communicate with far NOMA users to form qualified D2D connection with assistance of the Relay user ( R U ). The main metric in such CR-D2DNOMA network needs to be considered and we particularly introduce the closed-form expressions for outage probability in the secondary network where it is designed to serve two far NOMA users. The perfect Successive Interference Cancellation (SIC) and imperfect SIC can be further examined at the second NOMA user who detects signal based on the ability of SIC. The results show the positive impact of increasing the fading parameters on the system performance. More importantly, numerical results are provided to verify the correctness of our derivations. Additionally, the effects of asymptotic expressions on insights evaluation are also further analyzed.

scholarly journals Secure Beamforming in 5G-Based Cognitive Radio Network

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1260
Author(s):  
Hyils Sharon Magdalene Antony ◽  
Thulasimani Lakshmanan
Keyword(s):  
Cognitive Radio ◽  
Information Exchange ◽  
Cognitive Radio Network ◽  
Multiple Input Multiple Output ◽  
Primary User ◽  
Radio Network ◽  
Secrecy Rate ◽  
Secondary Users ◽  
Input Multiple Output ◽  
The Impact

Cognitive radio network (CRN) and non-orthogonal multiple-access (NOMA) is a significant system in the 5G wireless communication system. However, the system is an exceptional way for the cognitive users to secure a communication from the interferences in multiple-input multiple-output (MIMO)-NOMA-based cognitive radio network. In this article, a new beamforming technique is proposed to secure an information exchange within the same cells and neighboring cells from all intervened users. The interference is caused by an imperfect spectrum sensing of the secondary users (SUs). The SUs are intended to access the primary channels. At the same time, the primary user also returns to the channel before the SUs access ends. This similar way of accessing the primary channel will cause interference between the users. Thus, we predicted that the impact of interferences would be greatly reduced by the proposed technique, and that the proposed technique would maximize the entire secrecy rate in the 5G-based cognitive radio network. The simulation result provides better evidence for the performance of the proposed technique.

scholarly journals Detection of Malicious Primary User Emulation Based on a Support Vector Machine for a Mobile Cognitive Radio Network Using Software-Defined Radio

Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1282
Author(s):  
Ernesto Cadena Muñoz ◽  
Luis Fernando Pedraza Martínez ◽  
Jorge Eduardo Ortiz Triviño
Keyword(s):  
Support Vector Machine ◽  
Cognitive Radio ◽  
Software Defined Radio ◽  
Denial Of Service ◽  
Primary User ◽  
Support Vector ◽  
Electromagnetic Spectrum ◽  
Secondary Users ◽  
Low Snr ◽  
Primary User Emulation

Mobile cognitive radio networks provide a new platform to implement and adapt wireless cellular communications, increasing the use of the electromagnetic spectrum by using it when the primary user is not using it and providing cellular service to secondary users. In these networks, there exist vulnerabilities that can be exploited, such as the malicious primary user emulation (PUE), which tries to imitate the primary user signal to make the cognitive network release the used channel, causing a denial of service to secondary users. We propose a support vector machine (SVM) technique, which classifies if the received signal is a primary user or a malicious primary user emulation signal by using the signal-to-noise ratio (SNR) and Rényi entropy of the energy signal as an input to the SVM. This model improves the detection of the malicious attacker presence in low SNR without the need for a threshold calculation, which can lead to false detection results, especially in orthogonal frequency division multiplexing (OFDM) where the threshold is more difficult to estimate because the signal limit values are very close in low SNR. It is implemented on a software-defined radio (SDR) testbed to emulate the environment of mobile system modulations, such as Gaussian minimum shift keying (GMSK) and OFDM. The SVM made a previous learning process to allow the SVM system to recognize the signal behavior of a primary user in modulations such as GMSK and OFDM and the SNR value, and then the received test signal is analyzed in real-time to decide if a malicious PUE is present. The results show that our solution increases the detection probability compared to traditional techniques such as energy or cyclostationary detection in low SNR values, and it detects malicious PUE signal in MCRN.

A new transmission model in cognitive radio based on cyclic generalized polynomial codes for bandwidth reduction

2014 ◽  
Vol 06 (04) ◽  
pp. 1450059 ◽  
Author(s):  
Naveed Ahmed Azam ◽  
Tariq Shah ◽  
Antonio Aparecido de Andrade
Keyword(s):  
Cognitive Radio ◽  
Data Transmission ◽  
Primary User ◽  
Transmission Model ◽  
Secondary Users ◽  
Proposed Model ◽  
Generalized Polynomial ◽  
Polynomial Codes ◽  
Full Utilization ◽  
Minimum Interference

The frequency spectrums are inefficiently utilized and cognitive radio has been proposed for full utilization of these spectrums. The central idea of cognitive radio is to allow the secondary user to use the spectrum concurrently with the primary user with the compulsion of minimum interference. However, designing a model with minimum interference is a challenging task. In this paper, a transmission model based on cyclic generalized polynomial codes discussed in [2] and [15], is proposed for the improvement in utilization of spectrum. The proposed model assures a non interference data transmission of the primary and secondary users. Furthermore, analytical results are presented to show that the proposed model utilizes spectrum more efficiently as compared to traditional models.

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