Detection of primary user emulation attack based on modified adaptive orthogonal matched pursuit for cognitive radio networks in HCRAN

Odwa, Lilly Abau Yosia; Chen, Yueyun; Mai, Zhiyuan

doi:10.1145/3321408.3326667

Cited by 1 publication

(3 citation statements)

References 13 publications

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“…The simulation results for the EE are shown in Figure 7. According to equation (30), as SE increases, the EE should increase as well. However, the EE will decrease with increase in power of active users.…”

Section: Discussionmentioning

confidence: 99%

“…The modified adaptive orthogonal matching pursuit (MAOMP) was proposed as a gesture recognition algorithm [29]. Nevertheless, MAOMP has been proposed to detect PUEAs in cognitive radio network heterogeneous-CRAN (H-CRAN) [30]. In order to decrease the number of measurements to some extent and improve accuracy, the MAOMP method adopts sparsity estimation along with adjustable step size [29].…”

Section: Related Workmentioning

confidence: 99%

“…In order to evaluate equation ( 23), the RIP is utilized. The goal is to reconstruct the Φ G×M matrix in order to obtain a guaranteed unique solution provided that it obeys the RIP as expressed in [30,31,40]…”

Section: Performance Evaluationmentioning

confidence: 99%

See 2 more Smart Citations

Enhancing Spectral and Energy Efficiencies in a Cognitive Radio CRAN with PUEAs

Odwa

Chen

2023

Wireless Communications and Mobile Computing

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In a cloud radio access network, malicious users mitigate the attributes of primary users in order to occupy a specific idle spectrum band by sending false signals or carry out a denial of service attack. Moreover, with the increase in number of users and limited spectral and energy resources, the malicious users will compete for the spectrum with legitimate users, thus resulting in increase in spectrum scarcity problem. The most widely used defense approach against malicious users is the received signal strength method. However, harmful users can still imitate signal attributes and transmit powers of the primary users. Therefore, in order to elaborate the best method to tackle this vulnerability and hence make more spectrum available, the modified adaptive orthogonal matching pursuit localization algorithm is proposed to detect harmful users existing in the network. However, in order to elaborate the convergence speed of the proposed method, the regularized particle filter algorithm is applied to evaluate the performance of the modified adaptive orthogonal matching pursuit under real-time conditions. The restricted isometry property is used for the performance evaluation. Further, spectral and energy efficiencies are used in the simulation results for performance evaluation, in order to observe spectrum and energy utilization efficiencies. The simulation results show that the proposed method is better in terms of computational complexity, spectral efficiency, and energy efficiency compared to other matching pursuit approaches.

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Section: Discussionmentioning

confidence: 99%