Secure Spectrum Sensing in Cognitive-Radio-Based Smart Grid Using Role-Based Delegation

2016 ◽  
Author(s):  
Nedaa Al Hussien ◽  
Ezedin Barka ◽  
Mohammed Abdel-Hafez ◽  
Khaled Shuaib
Keyword(s):  
Cognitive Radio ◽  
Smart Grid ◽  
Spectrum Sensing ◽  
Role Based

scholarly journals Fuzzy-based reliable and secure cooperative spectrum sensing for the smart grid

2021 ◽  
Vol 8 (2) ◽  
pp. 92-100
Author(s):  
Laila Nassef ◽  
Reemah Alhebshi ◽  
Keyword(s):  
Cognitive Radio ◽  
Smart Grid ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Probability Of Detection ◽  
Fusion Center ◽  
Secondary Users ◽  
Sensing Data ◽  
Spectrum Detection ◽  
Fuzzy Fusion

Cognitive radio is a promising technology to solve the spectrum scarcity problem caused by inefficient utilization of radio spectrum bands. It allows secondary users to opportunistically access the underutilized spectrum bands assigned to licensed primary users. The local individual spectrum detection is inefficient, and cooperative spectrum sensing is employed to enhance spectrum detection accuracy. However, cooperative spectrum sensing opens up opportunities for new types of security attacks related to the cognitive cycle. One of these attacks is the spectrum sensing data falsification attack, where malicious secondary users send falsified sensing reports about spectrum availability to mislead the fusion center. This internal attack cannot be prevented using traditional cryptography mechanisms. To the best of our knowledge, none of the previous work has considered both unreliable communication environments and the spectrum sensing data falsification attack for cognitive radio based smart grid applications. This paper proposes a fuzzy inference system based on four conflicting descriptors. An attack model is formulated to determine the probability of detection for both honest and malicious secondary users. It considers four independent malicious secondary users’ attacking strategies of always yes, always no, random, and opposite attacks. The performance of the proposed fuzzy fusion system is simulated and compared with the conventional fusion rules of AND, OR, Majority, and the reliable fuzzy fusion that does not consider the secondary user’s sensing reputation. The results indicate that incorporating sensing reputation in the fusion center has enhanced the accuracy of spectrum detection and have prevented malicious secondary users from participating in the spectrum detection fusion

scholarly journals Demand Response Management Research Based on Cognitive Radio for Smart Grid

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Tingting Yang ◽  
Tiancong Huang ◽  
Haifeng Zhang ◽  
Peiyi Li ◽  
Canyun Xiong ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Smart Grid ◽  
Outage Probability ◽  
Spectrum Sensing ◽  
Demand Response ◽  
Loss Rate ◽  
Energy Detection ◽  
Detection Algorithm ◽  
System Control ◽  
Control Performance

Cognitive radio is introduced into the demand response management (DRM) of smart grid with the hope of alleviating the shortage of spectrum resources and improving communication quality. In this paper, we adopt an energy detection algorithm based on generalized stochastic resonance (GSRED) to improve the spectrum sensing accuracy under the circumstances of low signal-to-noise ratio without increasing system overhead. Specifically, a DRM scheme based on real-time pricing is investigated, and the social welfare is taken as the main index to measure system control performance. Furthermore, considering the adverse effects incurred by incorrect spectrum sensing, we incorporate the probability of the DRM system causing interference to primary user and spectrum loss rate into the evaluation index of the system control performance and give the final expression of the global optimization problem. The influence of sensing time on system communication outage probability and spectrum loss rate is elaborated in detail through theoretical derivation and simulation analysis. Simulation results show that the GSRED algorithm has higher detection probability under the same conditions compared with the traditional energy detection algorithm, thus guaranteeing lower communication outage probability and spectrum loss rate.

Energy Efficiency in Cognitive Radio Network: Green Technology Towards Next Generation Networks

2016 ◽  
Vol 5 (1) ◽  
pp. 45
Author(s):  
Seetaiah Kilaru ◽  
Adithya Gali
Keyword(s):  
Energy Efficiency ◽  
Cognitive Radio ◽  
Smart Grid ◽  
Power Allocation ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Power Grid ◽  
Mobile Network ◽  
Radio Network ◽  
Data Rates

Energy efficiency of mobile network is always a challenging task. From the past decade, it is observable that the users who are using multimedia services are increasing in rapid way. These multimedia applications require higher data rates. High data rates will consume more energy of mobile network, which results poor energy efficiency. To meet higher data rates and to achieve energy efficiency, Cognitive Mobile Network with small cell model was explained in this paper. Dynamics of the power grid also have significant impact on mobile networks, hence smart grid implementation was proposed instead of traditional power grid. Most of the existed studies on cognitive mobile network focussed on spectrum sensing only. This paper focussed on cognitive radio network implementation by considering spectrum sensing and smart grid environment. An iterative algorithm was proposed to attain equillibrium condition to the problem. Interference management and energy efficient power allocation were achieved with the introduction of smart grid. Simulation results proved that optimum power allocation and energy efficiency are possible with the introduction of smart grid in cognitive network.

In-band Spectrum Sensing without Quiet Period for OFDM System in Cognitive Radio

2011 ◽  
Vol 30 (11) ◽  
pp. 2638-2641
Author(s):  
Dong Chen ◽  
Jian-dong Li ◽  
Ji-yong Pang ◽  
Jing Ma
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Band Spectrum ◽  
Quiet Period ◽  
Ofdm System

An Energy Efficient Spectrum Aware Routing for Cognitive Radio Networks (CRNs)

2020 ◽  
Vol 10 ◽  
Author(s):  
Dileep Reddy Bolla ◽  
Jijesh J J ◽  
Mahaveer Penna ◽  
Shiva Shankar
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Energy Efficient ◽  
Research Work ◽  
Spectrum Management ◽  
Residual Energy ◽  
Radio Networks ◽  
Traffic Load ◽  
The Impact

Back Ground/ Aims:: Now-a-days in the Wireless Communications some of the spectrum bands are underutilized or unutilized; the spectrum can be utilized properly by using the Cognitive Radio Techniques using the Spectrum Sensing mechanisms. Objectives:: The prime objective of the research work carried out is to achieve the energy efficiency and to use the spectrum effectively by using the spectrum management concept and achieve better throughput, end to end delay etc., Methods:: The detection of the spectrum hole plays a vital role in the routing of Cognitive Radio Networks (CRNs). While detecting the spectrum holes and the routing, sensing is impacted by the hidden node issues and exposed node issues. The impact of sensing is improved by incorporating the Cooperative Spectrum Sensing (CSS) techniques. Along with these issues the spectrum resources changes time to time in the routing. Results:: All the issues are addressed with An Energy Efficient Spectrum aware Routing (EESR) protocol which improves the timeslot and the routing schemes. The overall network life time is improved with the aid of residual energy concepts and the overall network performance is improved. Conclusion:: The proposed protocol (EESR) is an integrated system with spectrum management and the routing is successfully established to communication in the network and further traffic load is observed to be balanced in the protocol based on the residual energy in a node and further it improves the Network Lifetime of the Overall Network and the Individual CR user, along with this the performance of the proposed protocol outperforms the conventional state of art routing protocols.

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