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Relevant bibliographies by topics / Cognitive radio transmitter

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Journal articles

Academic literature on the topic 'Cognitive radio transmitter'

Author: Grafiati

Published: 25 May 2024

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Journal articles on the topic "Cognitive radio transmitter"

1

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 charact

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2

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 er

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3

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 im

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4

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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5

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 re

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6

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 Prim

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7

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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8

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

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9

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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10

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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