scholarly journals PERFORMANCE ENHANCEMENTS OF COGNITIVE RADIO NETWORKS USING THE IMPROVED FUZZY LOGIC

2019 ◽  
Vol 2019 (2) ◽  
pp. 57-68 ◽  
Author(s):  
Dr. P Ebby Darney ◽  
Dr. I. Jeena Jacob
Keyword(s):  
Fuzzy Logic ◽  
Cognitive Radio ◽  
Spectrum Allocation ◽  
Network Simulator ◽  
Channel Switching ◽  
Secondary Users ◽  
Efficient Management ◽  
User Request ◽  
Radio Technology ◽  
Effective Decision

The rapid increase in the mobile device and the different types of wireless communication has led to the necessity of the extra spectrum allocation for the proper transmission of the information. Since the additional spectrum allocation for every network involved in the data transmission is a strenuous process, the efficient management of the spectrum allocation is preferred. The cognitive radio technology does a befitting service in the managing the allocation of the spectrum efficiently by providing the vacant spaces of the licensed users to the secondary users and vacating the secondary users when the licensed user request for the spectrum. This results in the deterioration in the performance of the secondary users due to the immediate evacuating. The conventional methods in the deciding the channel switching remains unsuitable for the cognitive radio network, so to have an effective decision on switching and selecting the channel the paper put forth the improved fuzzy logic that relies on the decision (IFDSS-GA) support system to handle both the switching of the channels and genetic algorithm to select the proper spectrum for conveyance. The evaluation of the proposed approach using the network simulator -2 determines the competency the IFDSS in terms of the throughput and switching rate.

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.

scholarly journals Reinforcement Learning-Based Routing Protocol to Minimize Channel Switching and Interference for Cognitive Radio Networks

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-24
Author(s):  
Tauqeer Safdar Malik ◽  
Mohd Hilmi Hasan
Keyword(s):  
Reinforcement Learning ◽  
Cognitive Radio ◽  
Routing Protocol ◽  
Channel Selection ◽  
Network Simulator ◽  
Mac Layer ◽  
Channel Switching ◽  
Network Layer ◽  
Switching Event ◽  
Channel Information

In the existing network-layered architectural stack of Cognitive Radio Ad Hoc Network (CRAHN), channel selection is performed at the Medium Access Control (MAC) layer. However, routing is done on the network layer. Due to this limitation, the Secondary/Unlicensed Users (SUs) need to access the channel information from the MAC layer whenever the channel switching event occurred during the data transmission. This issue delayed the channel selection process during the immediate routing decision for the channel switching event to continue the transmission. In this paper, a protocol is proposed to implement the channel selection decisions at the network layer during the routing process. The decision is based on past and expected future routing decisions of Primary Users (PUs). A learning agent operating in the cross-layer mode of the network-layered architectural stack is implemented in the spectrum mobility manager to pass the channel information to the network layer. This information is originated at the MAC layer. The channel selection is performed on the basis of reinforcement learning algorithms such as No-External Regret Learning, Q-Learning, and Learning Automata. This leads to minimizing the channel switching events and user interferences in the Reinforcement Learning- (RL-) based routing protocol. Simulations are conducted using Cognitive Radio Cognitive Network simulator based on Network Simulator (NS-2). The simulation results showed that the proposed routing protocol performed better than all the other comparative routing protocols in terms of number of channel switching events, average data rate, packet collision, packet loss, and end-to-end delay. The proposed routing protocol implies the improved Quality of Service (QoS) of the delay sensitive and real-time networks such as Cellular and Tele Vision (TV) networks.

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.

A SURVEY OF IMPLEMENTATION OF OPPORTUNISTIC SPECTRUM ACCESS ATTACK WITH ITS PREVENTIVE SENSING PROTOCOLS IN COGNITIVE RADIO NETWORKS

2015 ◽  
Vol 3 (6) ◽  
pp. 389
Author(s):  
Monisha Ravi ◽  
Nisha Ravi ◽  
N. Ravi
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Primary User ◽  
Radio Spectrum ◽  
Radio Networks ◽  
Spectrum Efficiency ◽  
Network Simulator ◽  
Secondary Users ◽  
Primary User Emulation Attack ◽  
Research Areas

Recently, the expansive growth of wireless services, regulated by governmental agencies assigning spectrum to licensed users, has led to a shortage of radio spectrum. Since the FCC (Federal Communications Commissions) approved unlicensed users to access the unused channels of the reserved spectrum, new research areas seeped in, to develop Cognitive Radio Networks (CRN), in order to improve spectrum efficiency and to exploit this feature by enabling secondary users to gain from the spectrum in an opportunistic manner via optimally distributed traffic demands over the spectrum, so as to reduce the risk for monetary loss, from the unused channels. However, Cognitive Radio Networks become vulnerable to various classes of threats that decrease the bandwidth and spectrum usage efficiency. Hence, this survey deals with defining and demonstrating framework of one such attack called the Primary User Emulation Attack and suggests preventive Sensing Protocols to counteract the same. It presents a scenario of the attack and its prevention using Network Simulator-2 for the attack performances and gives an outlook on the various techniques defined to curb the anomaly.

scholarly journals A Novel Binary Slime Mould Algorithm with AU Strategy for Cognitive Radio Spectrum Allocation

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Ling Li ◽  
Tien-Szu Pan ◽  
Xiao-Xue Sun ◽  
Shu-Chuan Chu ◽  
Jeng-Shyang Pan
Keyword(s):  
Cognitive Radio ◽  
Radio Spectrum ◽  
Spectrum Allocation ◽  
The Novel ◽  
Allocation Scheme ◽  
Network Resources ◽  
Allocation Model ◽  
Slime Mould ◽  
Radio Technology ◽  
Cognitive Radio Technology

AbstractSpectrum has now become a scarce resource due to the continuous development of wireless communication technology. Cognitive radio technology is considered to be a new method to solve the shortage of spectrum resources. The spectrum allocation model of cognitive radio can effectively avoid the waste of spectrum resources. A novel binary version of slime mould algorithm is proposed for the spectrum allocation model to solve the spectrum allocation scheme. In addition, adding unselected factors strategy can make the approach find a better solution. Compared with other algorithms, the novel binary slime mould algorithm and the strategy of adding unselected factors proposed in this paper have a good performance in spectrum allocation. The resulting spectrum allocation scheme can achieve efficient use of network resources.

Sign in / Sign up

Export Citation Format

Share Document