2009
DOI: 10.1109/twc.2009.080884
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Cognitive Radio game for secondary spectrum access problem

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Cited by 128 publications
(70 citation statements)
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“…For instance, the counter-measures to SSDF attacks include deploying a reputation metric to denote the scale of trustworthiness of each user [7], or reporting continuous sensing result to minimal attacks [8]. Game theory and Q-learning algorithm are often utilized to discuss attacker-SU action patterns [9] and to detect selfish users [10]. In confront of common control channel jamming attack, traditional communication technique of channel hopping is proved efficient for SUs exchanging channel information via multiple common control channels stochastically [11].…”
Section: Background and Related Workmentioning
confidence: 99%
“…For instance, the counter-measures to SSDF attacks include deploying a reputation metric to denote the scale of trustworthiness of each user [7], or reporting continuous sensing result to minimal attacks [8]. Game theory and Q-learning algorithm are often utilized to discuss attacker-SU action patterns [9] and to detect selfish users [10]. In confront of common control channel jamming attack, traditional communication technique of channel hopping is proved efficient for SUs exchanging channel information via multiple common control channels stochastically [11].…”
Section: Background and Related Workmentioning
confidence: 99%
“…The comparison between cooperative and noncooperative approaches has been presented in [16] through game theoretical analysis. The authors of [17] develop the optimal resource allocation strategies in secondary spectrum access problem using cooperative game theory. This work applies the concept of Nash bargaining solution to guarantee fairness and maximize the utility of the system optimality.…”
Section: Background and Related Workmentioning
confidence: 99%
“…The transmit power of an SU is equal to 0.01 W, and the additive white Gaussian noise (AWGN) with zero mean and variance σ 2 = 10 −11 W is considered at the input of the receiver. For SU i , its SNR can be calculated by (17), where P i is the transmit power of SU i , and d i is the distance between SU i and PU:…”
Section: The Nbmf-pso Algorithmmentioning
confidence: 99%
“…The primary network has a base station (e.g., cellular systems [26], TV broadcast networks [27]), whose location is known by the CR network, and multiple users, which are uniformly distributed across the network. In addition, this primary network has a requirement on the detection probability of the CR network in order to guarantee that its QoS will not be degraded due to allowing opportunistic access for SUs.…”
Section: System Modelmentioning
confidence: 99%