DocumentCode :
3200175
Title :
Optimal defense synthesis for jamming attacks in cognitive radio networks via swarm optimization
Author :
Zhang, Haopeng ; Liu, Zhenyi ; Hui, Qing
Author_Institution :
Dept. of Mech. Eng., Texas Tech Univ., Lubbock, TX, USA
fYear :
2012
fDate :
11-13 July 2012
Firstpage :
1
Lastpage :
8
Abstract :
In this paper, the optimal cognitive network reconfiguration problem is considered in the presence of jamming interference and delayed signals in a game play scenario. In most previous literature, only one jammer is investigated. However, in practical applications, multiple jammers occur frequently. Moreover, the delay of signals cannot be neglected in the context of network communication, which may result in an unstable system. Therefore, we formulate the optimization problem for network reconfiguration with multiple jammer´s interference and delayed signals. To solve the optimization problem numerically, two types of swarm optimization algorithms are proposed. In the first approach, the dynamic objective method is used via bilevel programming while in the second approach, a hybrid multiagent swarm optimization algorithm is applied. Some illustration results are also provided in the paper.
Keywords :
cognitive radio; jamming; particle swarm optimisation; radio networks; radiofrequency interference; bilevel programming; delayed signals; hybrid multiagent swarm optimization algorithm; jamming attacks; multiple jammer interference; network communication; optimal cognitive radio network reconfiguration problem; optimal defense synthesis; optimization problem; particle swarm optimization algorithm; Algorithm design and analysis; Heuristic algorithms; Jamming; Linear programming; Optimization; Particle swarm optimization; Topology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence for Security and Defence Applications (CISDA), 2012 IEEE Symposium on
Conference_Location :
Ottawa, ON
Print_ISBN :
978-1-4673-1416-9
Type :
conf
DOI :
10.1109/CISDA.2012.6291525
Filename :
6291525
Link To Document :
بازگشت