COLLABORATIVE SPECTRUM SENSING TECHNIQUE ASHISH BAGWA RIA ND GEETA M SINGH TOM A R

2014 ◽  
pp. 217-250
Keyword(s):  
Spectrum Sensing ◽  
Collaborative Spectrum Sensing

Exploiting Radio Correlation and Reliability Information in Collaborative Spectrum Sensing

2011 ◽  
Vol 15 (8) ◽  
pp. 825-827 ◽  
Author(s):  
William C. Headley ◽  
V. Gautham Chavali ◽  
Claudio R. C. M. da Silva
Keyword(s):  
Spectrum Sensing ◽  
Collaborative Spectrum Sensing

scholarly journals Evolutionary Game Theory-Based Collaborative Sensing Model in Emergency CRAHNs

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Sasirekha GVK ◽  
Jyotsna Bapat
Keyword(s):  
Game Theory ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Evolutionary Game Theory ◽  
Ad Hoc ◽  
Evolutionary Game ◽  
Autonomous Systems ◽  
Simulation Models ◽  
Signal To Noise ◽  
Collaborative Spectrum Sensing

Game theory has been a tool of choice for modeling dynamic interactions between autonomous systems. Cognitive radio ad hoc networks (CRAHNs) constituted of autonomous wireless nodes are a natural fit for game theory-based modeling. The game theory-based model is particularly suitable for “collaborative spectrum sensing” where each cognitive radio senses the spectrum and shares the results with other nodes such that the targeted sensing accuracy is achieved. Spectrum sensing in CRAHNs, especially when used in emergency scenarios such as disaster management and military applications, needs to be not only accurate and resource efficient, but also adaptive to the changing number of users as well as signal-to-noise ratios. In addition, spectrum sensing mechanism must also be proactive, fair, and tolerant to security attacks. Existing work in collaborative spectrum sensing has mostly been confined to resource efficiency in static systems using request-based reactive sensing resulting in high latencies. In this paper, evolutionary game theory (EGT) is used to model the behavior of the emergency CRAHNS, providing an efficient model for collaborative spectrum sensing. The resulting implementation model is adaptive to the changes in its environment such as signal-to-noise ratio and number of users in the network. The analytical and simulation models presented validate the system design and the desired performance.

Byzantine Attacker Identification in Collaborative Spectrum Sensing: A Robust Defense Framework

2019 ◽  
Vol 18 (9) ◽  
pp. 1992-2004 ◽  
Author(s):  
Linyuan Zhang ◽  
Guangming Nie ◽  
Guoru Ding ◽  
Qihui Wu ◽  
Zhaoyang Zhang ◽  
...  
Keyword(s):  
Spectrum Sensing ◽  
Collaborative Spectrum Sensing
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