Bibliografías temáticas / Cognitive radio transmitter

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Literatura académica sobre el tema "Cognitive radio transmitter"

Autor: Grafiati

Publicado: 25 de mayo de 2024

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Artículos de revistas sobre el tema "Cognitive radio transmitter"

Lafia, Diafale, Mistura Laide Sanni, Rasheed Ayodeji Adetona, Bodunde Odunola Akinyemi, and Ganiyu Adesola Aderounmu. "Signal Processing-based Model for Primary User Emulation Attacks Detection in Cognitive Radio Networks." Journal of Computing and Information Technology 29, no. 2 (2022): 77–88. http://dx.doi.org/10.20532/cit.2021.1005297.

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Cognitive Radio Networks (CRNs) have been conceived to improve the efficiency of accessing the spectrum. However, these networks are prone to various kinds of attacks and failures that can compromise the security and performance of their users. One of the notable malicious attacks in cognitive radio networks is the Primary User Emulation (PUE) attack, which results in underutilization and unavailability of the spectrum and low operational efficiency of the network. This study developed an improved technique for detecting PUE attacks in cognitive radio networks and further addressed the characteristics of sparsely populated cognitive radio networks and the mobility of the primary users. A hybrid signal processing-based model was developed using the free space path loss and additive Gaussian noise models. The free space path loss model was used to detect the position of the transmitter, while the additive Gaussian noise model was used to analyze the signal transmitted, i.e., energy detection in the spectrum at the detected location. The proposed model was benchmarked with an existing model using the number of secondary users and the velocity of the transmitter as performance parameters. The simulation results show that the proposed model has improved accuracy in detecting primary user emulation attacks. It was concluded that the proposed hybrid model with respect to the number of secondary users and the velocity of the transmitter can be used for primary user emulation attack detection in cognitive radio networks.

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Oni, Phillip Babatunde, Ruifeng Duan, and Mohammed Elmusrati. "Dual Analysis of the Capacity of Spectrum Sharing Cognitive Radio with MRC under Nakagami-m Fading." Conference Papers in Engineering 2013 (May 28, 2013): 1–8. http://dx.doi.org/10.1155/2013/572383.

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In this study, the maximum achievable information transmission rate of spectrum sharing cognitive radio with maximal ratio combining (MRC) antenna diversity technique is investigated when the channel between the secondary transmitter and the primary receiver and that between the secondary transmitter and the secondary receiver suffer Nakagami-m fading. With an assumption that both channels encounter Nakagami-m fading and the transmission of the secondary transmitter is subject to average interference power constraint, the approximated expressions for analyzing the effective capacity and the ergodic capacity of cognitive radio users with MRC are presented. The two capacity models are compared. In the case of the effective capacity, it is shown that different applications or users with different quality of service (QoS) requirements can be supported in cognitive radio, and when the delay QoS decreases, the effective capacity approaches the ergodic capacity.

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Rahman, Md Zia Ur, P. V. S. Aswitha, D. Sriprathyusha, and S. K. Sameera Farheen. "Beamforming in cognitive radio networks using partial update adaptive learning algorithm." ACTA IMEKO 11, no. 1 (2022): 8. http://dx.doi.org/10.21014/acta_imeko.v11i1.1214.

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<p>Cognitive radio technology is a promising way to improve bandwidth efficiency. Frequency which is not used in any aspect will be utilized by using some of the most powerful resources in this cognitive radio. One of the main advantages of cognitive radio signal is to detect the different channels which are there in the spectrum and it can modify the frequencies which is utilized frequently. It allows the licensed users to gain the licensed bandwidth under the condition to protect the licensed users from harmful interference i.e., from secondary users. In this paper, we would like to implement cognitive radio using the beamforming technique, by using power allocation as a strategy for the unlicensed transmitter which is purely form on the result of sensing. It is on the state of the primary user in a various cognitive radio network whereas the unlicensed transmitter gives a single antenna and it modify its power transmission. For the cognitive radio setup, we have used normalized adaptive learning algorithms. This application would be very useful in medical telemetry applications. Nowadays wireless communication plays a vital role in healthcare applications for that we have to build a separate base. It reduces the effort of the building of separate infrastructure for medical telemetry applications.</p>

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Lin, Pin-Hsun, Shih-Chun Lin, Chung-Pi Lee, and Hsuan-Jung Su. "Cognitive Radio with Partial Channel State Information at the Transmitter." IEEE Transactions on Wireless Communications 9, no. 11 (2010): 3402–13. http://dx.doi.org/10.1109/twc.2010.092410.090725.

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Goel, Paurav, Avtar Singh, and Ashok Goel. "Transmit power control and data rate enhancement in cognitive radio network using computational intelligence." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 2 (2022): 1602. http://dx.doi.org/10.11591/ijece.v12i2.pp1602-1616.

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Underutilized radio frequencies are the chief apprehension in advance radio communication. The radio recourses are sparse and costly and their efficient allocation has become a challenge. Cognitive radio networks are the ray of hope. Cognitive radio networks use dynamic spectrum access technique to opportunistically retrieve and share the licensed spectrum. The licensed users are called primary users and the users that opportunistically access the licensed spectrum all called secondary users. The proposed system is a feedback system that work on demand and supply concept, in which secondary receivers senses the vacant spectrum and shares the information with the secondary transmitters. The secondary transmitters adjust their transmission parameters of transmit power and data rate in such a way that date rate is maximized. Two methods of spectrum access using frequency division multiple access (FDMA) and Time division multiple access (TDMA) are discussed. Interference temperature limit and maximum achievable capacity are the constraints that regulate the entire technique. The aim of the technique is to control the transmitter power according to the data requirements of each secondary user and optimizing the resources like bandwidth, transmit power using machine learning and feed forward back propagation deep neural networks making full use of the network capacity without hampering the operation of primary network.

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Et. al., Dr Mahesh Kumar N,. "Analytical Model for Mitigating Primary User Emulation Attack using Hypothesis Testing in Cognitive Radio Networks." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 11 (2021): 486–500. http://dx.doi.org/10.17762/turcomat.v12i11.5912.

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The Cognitive Radio (CR) is the key technology to deal with spectrum scarcity by allowing unlicensed CR users to coexist with existing users in licensed spectrum bands without interfering with binding communications. Cognitive technology provides the spectrum ability to be shared with licensed networks. This radio system can adjust its transmitter and recipient parameters on the basis of interaction with the current conditions in the environment. Due to this flexibility cognitive radios are exploring different types of threats and security attacks. In this paper, we focus primarily on the Primary User Emulation Attack (PUEA) which is a major attack in the cognitive radio network. PUEA is similar to a Denial-of-service attack that can seriously disrupt the spectrum sensing process and deny other legitimate secondary users to access the available spectrum. We proposed a Neyman-Pearson composite hypothesis test (NPCHT) based analytical model to study the impact of PUEA in a fading wireless communication environment. Simulation results show that the proposed techniques can substantially reduce the impact of the malicious attack on the network

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Zhang, Xiaodong, Xiaowei Zhu, Jing Liu, and Changjiang You. "A low EVM zero-IF RF transmitter for cognitive radio application." Journal of Electronics (China) 27, no. 5 (2010): 723–27. http://dx.doi.org/10.1007/s11767-011-0500-5.

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Ammar, Mahmoud Ali. "Performance Metrics in Cognitive Radio Networks." AL-MUKHTAR JOURNAL OF SCIENCES 36, no. 1 (2021): 73–79. http://dx.doi.org/10.54172/mjsc.v36i1.21.

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In Cognitive Radio Networks (CRN), the main aim is to allow the secondary users (SUs) to identify the empty bands and use them to transmit or receive data opportunistically. Primary users (PUs) have the priority to use a channel, while the secondary users must vacant this channel once a primary user requests it. An attack known in cognitive radio networks as a Primary User Emulation Attack (PUEA) aims to prevent the SU from using the empty bands. In this paper, an analytical and experimental approach is presented to mitigate the PUEA. This approach is based on obtaining the Probability Density Functions (PDFs) of the received powers at the secondary users from malicious nodes and also from the primary transmitter in the cognitive network. Then, these obtained PDFs are used in Neyman-Pearson composite hypothesis test to measure the performance metrics (probability of false alarm and miss detection in the network). The results proved that the performance metrics were greatly influenced by the network area, where the secondary user is located, and the threshold value λ used in the decision rule. Also, there are boundaries for the λ choices that cannot be overtaken.

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UM, Jung-Sun, Sung-Hyun HWANG, Chang-Joo KIM, and Byung Jang JEONG. "A Novel Transmitter and Receiver Structure for Cognitive Radio Based OFDM Systems." IEICE Transactions on Communications E94-B, no. 4 (2011): 1070–71. http://dx.doi.org/10.1587/transcom.e94.b.1070.

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Tran, Hoai Trung. "Proposed Precoder for the Secondary Transmitter in the Cognitive MIMO Radio Network." International Journal of Computer Applications 183, no. 22 (2021): 20–26. http://dx.doi.org/10.5120/ijca2021921587.

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