A novel model for implicit cooperation between primary users and secondary users in cognitive radio-cooperative communication systems

2018 ◽  
Vol 31 (6) ◽  
pp. e3524 ◽  
Author(s):  
Montajab Ghanem ◽  
Masoud Sabaei ◽  
Mehdi Dehghan
Keyword(s):  
Cognitive Radio ◽  
Cooperative Communication ◽  
Communication Systems ◽  
Secondary Users ◽  
Primary Users ◽  
Novel Model

scholarly journals Optimal Power Allocation for MIMO-MAC in Cognitive Radio Networks

2021 ◽  
Author(s):  
Peter He ◽  
Guangming (Minco) He ◽  
Lian Zhao
Keyword(s):  
Cognitive Radio ◽  
Communication Systems ◽  
Multiple Input Multiple Output ◽  
Mobile User ◽  
Upper And Lower Bounds ◽  
Maximization Problem ◽  
Dual Decomposition ◽  
Secondary Users ◽  
Primary Users ◽  
Sum Rate

This paper considers a cognitive radio (CR) network, in which the unlicensed (secondary) users (SUs) are allowed to concurrently access the spectrum allocated to the licensed (primary) users, provided that the interference of SUs with the primary users (PUs) satisfies certain constraints. It is more general and owns a stronger challenge to ensure the quality of service (QoS) of PUs, as well as to maximize the sum-rate of SUs. On the other hand, the multiple-antenna mobile user case has not been well investigated for the target problem in the open literature. We refer to this setting as multiple input multiple output multiple access channels (MIMO-MAC) in the CR network. Subject to the interference constraints of SUs and the peak power constraints of SUs, the sum-rate maximization problem is solved. To efficiently maximize the achievable sum-rate of SUs, a tight pair of upper and lower bounds, as an interval, of the optimal Lagrange multiplier is proposed. It can avoid ineffectiveness or inefficiency when the dual decomposition is used. Furthermore, a novel water-filling-like algorithm is proposed for the inner loop computation of the proposed problem. It is shown that this algorithm used in the inner loop computation can obtain the exact solution with a few finite computations, to avoid one more loop, which would be embedded in the inner loop. In addition, the proposed approach overcomes the limitation of Hermitian matrices, as optimization variables. This limitation to the optimization problem in several complex variables has not been well investigated so far. As a result, our analysis and results are solidly extended to the field of complex numbers, which are more compatible with practical communication systems.

scholarly journals Optimal Power Allocation for MIMO-MAC in Cognitive Radio Networks

2021 ◽  
Author(s):  
Peter He ◽  
Guangming (Minco) He ◽  
Lian Zhao
Keyword(s):  
Cognitive Radio ◽  
Communication Systems ◽  
Multiple Input Multiple Output ◽  
Mobile User ◽  
Upper And Lower Bounds ◽  
Maximization Problem ◽  
Dual Decomposition ◽  
Secondary Users ◽  
Primary Users ◽  
Sum Rate

This paper considers a cognitive radio (CR) network, in which the unlicensed (secondary) users (SUs) are allowed to concurrently access the spectrum allocated to the licensed (primary) users, provided that the interference of SUs with the primary users (PUs) satisfies certain constraints. It is more general and owns a stronger challenge to ensure the quality of service (QoS) of PUs, as well as to maximize the sum-rate of SUs. On the other hand, the multiple-antenna mobile user case has not been well investigated for the target problem in the open literature. We refer to this setting as multiple input multiple output multiple access channels (MIMO-MAC) in the CR network. Subject to the interference constraints of SUs and the peak power constraints of SUs, the sum-rate maximization problem is solved. To efficiently maximize the achievable sum-rate of SUs, a tight pair of upper and lower bounds, as an interval, of the optimal Lagrange multiplier is proposed. It can avoid ineffectiveness or inefficiency when the dual decomposition is used. Furthermore, a novel water-filling-like algorithm is proposed for the inner loop computation of the proposed problem. It is shown that this algorithm used in the inner loop computation can obtain the exact solution with a few finite computations, to avoid one more loop, which would be embedded in the inner loop. In addition, the proposed approach overcomes the limitation of Hermitian matrices, as optimization variables. This limitation to the optimization problem in several complex variables has not been well investigated so far. As a result, our analysis and results are solidly extended to the field of complex numbers, which are more compatible with practical communication systems.

scholarly journals Deep Learning Predictive Models for Cognitive Radio System

2019 ◽  
Vol 9 (2S) ◽  
pp. 491-496
Keyword(s):  
Deep Learning ◽  
Cognitive Radio ◽  
Frequency Band ◽  
Communication Systems ◽  
Geographical Area ◽  
Data Sets ◽  
Secondary Users ◽  
Radio System ◽  
Primary Users ◽  
Accuracy Of Prediction

Cognitive Radio (CR) was introduced to improve the utilization of Radio Frequencies (RF) that remain under-utilized by the primary users (licensee). The main idea behind CR is to allow un-licensed (secondary) users to occupy vacancies in licensed bands. However, CR mandates the secondary user to vacate the frequency band within a specified time after the primary user attempts to use the frequency band. CR does not expect the primary users to share their frequency usage schedules and hence the secondary users have to scan and predict the vacancy. The advantage for the secondary users is that they do not pay for utilization of band, if they are conformal to the CR specifications. CR is the next generation of smart communication systems. CR requires continuous monitoring of the intended RF band in the intended geographical area. This information may be used to predict spectral vacancies (white spaces). Certain bands, e.g. Analog TV bands, will have pre declared utilization schedules but in general, spectrum utilization is a random process and hence prediction can be difficult. However, Deep Learning (DL) techniques can improve the accuracy of prediction. Deep Learning techniques require large and clean data sets to work correctly. Such data sets are also necessary to compare achievable accuracy of prediction algorithms. Towards this end, we have created data sets that can be used for simulation, training and testing of CR over GSM band (890-960MHz). A typical file with two hour of observations will have about 1.2 million samples. More than 1000 sets of data samples have been captured from urban and rural areas in India. All the data sets have been cleaned to avoid instrument errors and statistical outliers. In this paper we have used these standardized data sets to perform a comparative analysis of three DL methods for CR, viz. Auto-encoder (AE), Long Short-Term Memory (LSTM) and Multi Layer Perceptron (MLP). Results of the comparison are discussed.

Interference Modeling and Analysis in Cognitive Radio Networks

2013 ◽  
Vol 4 (4) ◽  
pp. 1-15
Author(s):  
Yanxiao Zhao ◽  
Bighnaraj Panigrahi ◽  
Kazem Sohraby ◽  
Wei Wang
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Critical Role ◽  
Radio Networks ◽  
Secondary Users ◽  
Idle State ◽  
Modeling And Analysis ◽  
Interference Modeling ◽  
Primary Users

Cognitive radio networks (CRNs) have received considerable attention and viewed as a promising paradigm for future wireless networking. Its major difference from the traditional wireless networks is that secondary users are allowed to access the channel if they pose no harmful interference to primary users. This distinct feature of CRNs has raised an essential and challenging question, i.e., how to accurately estimate interference to the primary users from the secondary users? In addition, spectrum sensing plays a critical role in CRNs. Secondary users have to sense the channel before they transmit. A two-state sensing model is commonly used, which classifies a channel into either busy or idle state. Secondary users can only utilize a channel when it is detected to be in idle state. In this paper, we tackle the estimation of interference at the primary receiver due to concurrently active secondary users. With the spectrum sensing, secondary users are refrained from transmitting once an active user falls into their sensing range. As a result, the maximum number of simultaneously interfering secondary users is bounded, typically ranging from 1 to 4. This significant conclusion considerably simplifies interference modeling in CRNs. The authors present all the cases with possible simultaneously interfering secondary users. Moreover, the authors derive the probability for each case. Extensive simulations are conducted and results validate the effectiveness and accuracy of the proposed approach.

scholarly journals Anti-Wiretap Spectrum-Sharing for Cooperative Cognitive Radio Communication Systems

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4142
Author(s):  
Peiyuan Si ◽  
Weidang Lu ◽  
Kecai Gu ◽  
Xin Liu ◽  
Bo Li ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Wireless Communication ◽  
Cooperative Communication ◽  
Communication Systems ◽  
Spectrum Sharing ◽  
Transmission Rate ◽  
Primary System ◽  
Radio Communication ◽  
Sharing Scheme ◽  
Simulation Results

As wireless communication technology keeps progressing, people’s requirements for wireless communication quality are getting higher and higher. Wireless communication brings convenience, but also causes some problems. On the one hand, the traditional static and fixed spectrum allocation strategy leads to high wastefulness of spectrum resources. The direction of improving the utility of spectrum resources by combining the advantages of cooperative communication and cognitive radio has attracted the attention of many scholars. On the other hand, security of communication is becoming an important issue because of the broadcasting nature and openness of wireless communication. Physical-layer security has been brought into focus due to the possibility of improving the security in wireless communication. In this paper, we propose an anti-wiretap spectrum-sharing scheme for cooperative cognitive radio communication systems which can secure the information transmission for the two transmission phases of the cooperative communication. We maximized the secondary system transmission rate by jointly optimizing power and bandwidth while ensuring the primary system achieves its secrecy transmission rate. Useful insights of the proposed anti-wiretap spectrum-sharing scheme are given in the simulation results. Moreover, several system parameters are shown to have a big impact for the simulation results.

QoS Maintenance in Cognitive Radio Networks with Priority-Supporting Novel Channel Allocation Method

2019 ◽  
Vol 15 (1) ◽  
pp. 1-16
Author(s):  
K. Annapurna ◽  
B. Seetha Ramanjaneyulu
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Channel Allocation ◽  
Radio Networks ◽  
Secondary Users ◽  
Primary Users ◽  
Maximum Value ◽  
Blocking Probabilities ◽  
Bid Price

Satisfying the Quality of Service (QoS) is often a challenge in cognitive radio networks, because they depend on opportunistic channel accessing. In this context, appropriate pricing of vacant channels that is linked to the preference in their allocation, is found to be useful. However, ambiguity on the possible price at which the channel would be allotted is still a concern. In this work, an auction mechanism in which maximum value of the bid is predefined is proposed. With this, users quote their bid values as per their needs of getting the channels, up to the predefined maximum allowed bid price. However, final price of allocation is decided based on the sum total demand from all the users and the availability of vacant channels. Performance of the system is found in terms of blocking probabilities of secondary users and revenues to primary users. The proposed system is found to yield similar quantum of revenues as that of the Generalized Second Price (GSP) auction, while offering much lesser blocking probabilities to high-priority users to satisfy their QoS requirements.

scholarly journals Bio-inspired route estimation in cognitive radio networks

2020 ◽  
Vol 10 (3) ◽  
pp. 3095
Author(s):  
Miguel Tuberquia ◽  
Hans Lopez-Chavez ◽  
Cesar Hernandez
Keyword(s):  
Cognitive Radio ◽  
Ant Colony Optimization ◽  
Cognitive Radio Networks ◽  
Radio Networks ◽  
Ant Colony ◽  
Secondary Users ◽  
Mobility Spectrum ◽  
Hybrid Strategy ◽  
Primary Users ◽  
Specific Radio

Cognitive radio is a technique that was originally created for the proper use of the radio electric spectrum due its underuse. A few methods were used to predict the network traffic to determine the occupancy of the spectrum and then use the ‘holes’ between the transmissions of primary users. The goal is to guarantee a complete transmission for the second user while not interrupting the trans-mission of primary users. This study seeks the multifractal generation of traffic for a specific radio electric spectrum as well as a bio-inspired route estimation for secondary users. It uses the MFHW algorithm to generate multifractal traces and two bio-inspired algo-rithms: Ant Colony Optimization and Max Feeding to calculate the secondary user’s path. Multifractal characteristics offer a predic-tion, which is 10% lower in comparison with the original traffic values and a complete transmission for secondary users. In fact, a hybrid strategy combining both bio-inspired algorithms promise a reduction in handoff. The purpose of this research consists on deriving future investigation in the generation of multifractal traffic and a mobility spectrum using bio-inspired algorithms.

scholarly journals Intelligent Process of Spectrum Handoff/Mobility in Cognitive Radio Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Prince Semba Yawada ◽  
Mai Trung Dong
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Communication Systems ◽  
Spectral Band ◽  
Spectrum Management ◽  
Radio Networks ◽  
Innovative Technology ◽  
Main Task ◽  
Secondary Users ◽  
Spectrum Handoff

Cognitive radio is an innovative technology in the field of wireless communication systems, aimed at significantly improving the use of the radio spectrum while allowing secondary users to access the spectral band opportunistically. Spectrum management mechanism ensures the transmission of data by controlling the efficiency of operation between the primary and secondary networks. The main task of spectrum management is to ensure that secondary users benefit from the spectrum without interfering with primary users. This paper deals with some of the important characteristics of spectrum mobility in the cognitive radio networks. The new management approaches of the mobility and the connection are designed to reduce the latency and loss of information during spectrum handoff, a list of channel safeguard is maintained in this effect, but the maintenance and update are a challenge. In this paper, we describe the reasons and mechanisms of spectrum handoff. Protocols have been developed to illustrate this handoff mechanism. We also make a comparison between the different methods of spectrum handoff. The simulation results obtained confirm that the protocols developed and the proposed method performed better than the pure reactive handoff method.

Towards Security Issues and Solutions in Cognitive Radio Networks

2015 ◽  
pp. 813-834
Author(s):  
Saed Alrabaee ◽  
Mahmoud Khasawneh ◽  
Anjali Agarwal
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Radio Networks ◽  
Network Technology ◽  
Spectrum Utilization ◽  
Secondary Users ◽  
Security Issues ◽  
Primary Users ◽  
Radio Technology ◽  
Cognitive Radio Technology

Cognitive radio technology is the vision of pervasive wireless communications that improves the spectrum utilization and offers many social and individual benefits. The objective of the cognitive radio network technology is to use the unutilized spectrum by primary users and fulfill the secondary users' demands irrespective of time and location (any time and any place). Due to their flexibility, the Cognitive Radio Networks (CRNs) are vulnerable to numerous threats and security problems that will affect the performance of the network. Little attention has been given to security aspects in cognitive radio networks. In this chapter, the authors discuss the security issues in cognitive radio networks, and then they present an intensive list of the main known security threats in CRN at various layers and the adverse effects on performance due to such threats, and the current existing paradigms to mitigate such issues and threats. Finally, the authors highlight proposed directions in order to make CRN more authenticated, reliable, and secure.

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