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Relevant bibliographies by topics / Networks with underlay cognitive nodes

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Academic literature on the topic 'Networks with underlay cognitive nodes'

Author: Grafiati

Published: 6 September 2023

Last updated: 31 July 2025

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Journal articles on the topic "Networks with underlay cognitive nodes"

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Hussain, Syed Imtiaz, Mohamed M. Abdallah, Mohamed-Slim Alouini, Khalid Qaraqe, and Mazen Hasna. "Relay selection in underlay cognitive networks with fixed transmission power nodes." Transactions on Emerging Telecommunications Technologies 24, no. 7-8 (2013): 734–47. http://dx.doi.org/10.1002/ett.2691.

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Abdulghafoor, Omar B., Mahamod Ismail, Rosdiadee Nordin, and Musbah Shaat. "Fast and Distributed Power Control Algorithm in Underlay Cognitive Radio Networks." Journal of Communications 9, no. 8 (2014): 634–43. https://doi.org/10.5281/zenodo.56435.

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The power allocation in an underlay cognitive radio network rises up several challenges due to rapid utilization of the available spectrum hole. In this paper, we propose a non-cooperative power-game algorithm to solve the power allocation problem in an underlay cognitive radio network with two main objectives: (i) to provide good quality of service to cognitive radio nodes, and (ii) to protect the transmission of primary users from the interference generated by nearby cognitive radio. These objectives have been assured by including the following constraints: transmit power on each cognitive n

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Alhamad, Raed, and Hatem Boujemaa. "Intelligent Reflecting Surfaces with Adaptive Transmit Power for Underlay Cognitive Radio Networks." Wireless Communications and Mobile Computing 2022 (August 17, 2022): 1–7. http://dx.doi.org/10.1155/2022/2787466.

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In this article, we study the performance of intelligent reflecting surfaces (IRS) with adaptive transmit power (ATP). The power of secondary source is adapted to have a low interference at primary destination. IRS with ATP offers 14, 20, 26, 32, and 38 dB gains versus the absence of IRS for N = 8,16,32,64 , and 128 reflectors. Rayleigh channels are studied with arbitrary positions of primary and secondary nodes.

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Toan, Hoang Van, and Vo Nguyen Quoc Bao. "Performance Analysis of Cognitive Two-Way Networks with Interference from Primary User over Nakagami-m Fading Channels." Journal of Science and Technology: Issue on Information and Communications Technology 3, no. 1 (2017): 29. http://dx.doi.org/10.31130/jst.2017.35.

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A cognitive underlay two-way relay network taking into account interference links from primary transmitter to secondary receivers over Nakagami-m fading channels is analyzed in this article. In this model, a secondary system including two terminal nodes exchanges data through a decode-and-forward (DF) relay node. Under the underlay approach, all secondary transmitter must adjust transmit power to protect the primary communications. We derive the exact and asymptotic closed-form expression for the secondary system outage probability over Nakagami-m fading channels showing the system diversity.

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Phu, Tran Tin, Ha Duy-Hung, Minh Quang Pham, Thanh Binh Nguyen, and Luong Nhat Nguyen. "Performance of multi-hop cognitive MIMO relaying networks with joint constraint of intercept probability and limited interference." TELKOMNIKA Telecommunication, Computing, Electronics and Control 19, no. 1 (2021): pp. 44~50. https://doi.org/10.12928/TELKOMNIKA.v19i1.18006.

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In this paper, we propose a multi-hop multiple input multiple output (MIMO) decode-and-forward relaying protocol in cognitive radio networks. In this protocol, a multi-antenna secondary source attempts to send its data to a multi antenna secondary destination with assistance of multiple intermediate multi antenna nodes, in presence of a multi-antenna secondary eavesdropper. A primary network includes a primary transmitter and a primary receiver which are equipped with multiple antennas, and use transmit antenna selection (TAS) and selection combining (SC) to communicate with each other. Operat

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Han, Xu, Lei Xue, Ying Xu, and Zunyang Liu. "A Radio Environment Maps Estimation Algorithm based on the Pixel Regression Framework for Underlay Cognitive Radio Networks Using Incomplete Training Data." Sensors 20, no. 8 (2020): 2245. http://dx.doi.org/10.3390/s20082245.

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In the underlay cognitive radio networks, the radio environment maps (REMs) estimation is the main challenge in sensing the idle wireless spectrum resources. Traditional deep learning-based algorithms estimate the REMs on the basis of the high-quality, large-scale complete training images. However, collecting the complete radio environment images is time-consuming and requires a numerous number of power spectrum sensing nodes. For this reason, we propose a generative adversarial networks-based pixel regression framework (PRF) for underlay cognitive radio networks. The PRF algorithm relaxes the

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Kozić, Nadica, Vesna Blagojević, Aleksandra Cvetković, and Predrag Ivaniš. "Performance Analysis of Wirelessly Powered Cognitive Radio Network with Statistical CSI and Random Mobility." Sensors 23, no. 9 (2023): 4518. http://dx.doi.org/10.3390/s23094518.

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The relentless expansion of communications services and applications in 5G networks and their further projected growth bring the challenge of necessary spectrum scarcity, a challenge which might be overcome using the concept of cognitive radio. Furthermore, an extremely high number of low-power devices are introduced by the concept of the Internet of Things (IoT), which also requires efficient energy usage and practically applicable device powering. Motivated by these facts, in this paper, we analyze a wirelessly powered underlay cognitive system based on a realistic case in which statistical

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Bakht, Khush, Furqan Jameel, Zain Ali, et al. "Power Allocation and User Assignment Scheme for beyond 5G Heterogeneous Networks." Wireless Communications and Mobile Computing 2019 (November 16, 2019): 1–11. http://dx.doi.org/10.1155/2019/2472783.

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The issue of spectrum scarcity in wireless networks is becoming prominent and critical with each passing year. Although several promising solutions have been proposed to provide a solution to spectrum scarcity, most of them have many associated tradeoffs. In this context, one of the emerging ideas relates to the utilization of cognitive radios (CR) for future heterogeneous networks (HetNets). This paper provides a marriage of two promising candidates (i.e., CR and HetNets) for beyond fifth generation (5G) wireless networks. More specifically, a joint power allocation and user assignment soluti

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Tran Tin, Phu, Dang The Hung, Tan Nguyen, Tran Duy, and Miroslav Voznak. "Secrecy Performance Enhancement for Underlay Cognitive Radio Networks Employing Cooperative Multi-Hop Transmission with and without Presence of Hardware Impairments." Entropy 21, no. 2 (2019): 217. http://dx.doi.org/10.3390/e21020217.

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In this paper, we consider a cooperative multi-hop secured transmission protocol to underlay cognitive radio networks. In the proposed protocol, a secondary source attempts to transmit its data to a secondary destination with the assistance of multiple secondary relays. In addition, there exists a secondary eavesdropper who tries to overhear the source data. Under a maximum interference level required by a primary user, the secondary source and relay nodes must adjust their transmit power. We first formulate effective signal-to-interference-plus-noise ratio (SINR) as well as secrecy capacity u

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K, Shashi Raj, K. Siddesh G, Mallikarjunaswamy S, and Vivek Raj K. "Interference resilient stochastic prediction based dynamic resource allocation model for cognitive MANETs." Indian Journal of Science and Technology 13, no. 41 (2020): 4332–50. https://doi.org/10.17485/IJST/v13i41.687.

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Abstract <strong>Background/Objectives</strong>: Being dynamic in nature, Mobile Ad-hoc Network (MANET) requires robust resource allocation strategy that can ensure both optimal transmission reliability and resource efficiency to meet Quality of Service (QoS) demands. The objective of this research is to address interference resilience requirement in MANETs which is must due to greedy nature of nodes especially when accessing resource or bandwidth and develop a highly robust stochastic prediction based resource allocation strategy. <strong>Methods</strong>: The proposed Interference Resil

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Dissertations / Theses on the topic "Networks with underlay cognitive nodes"

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Chakraborty, Pratik. "Improving secrecy and spectral utilization efficiency in networks with underlay cognitive nodes." Thesis, IIT Delhi, 2018. http://eprint.iitd.ac.in:80//handle/2074/8043.

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Jasbi, Fahimeh Jafarali. "Hybrid overlay/underlay cognitive radio networks with MC-CDMA." Thesis, University of Manchester, 2014. https://www.research.manchester.ac.uk/portal/en/theses/hybrid-overlayunderlay-cognitive-radio-networks-with-mccdma(435d45a5-82c0-4507-9c53-23aa248988c9).html.

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There has been a growing demand for wireless communication services in the past few years. Recent reports reveal that the demand will not only increase in the number of subscribers but also in more diverse applications such as Machine-to-Machine (M2M) communications and the Internet of Things. With such demand for capacity increase, there is a necessity to shift from today’s Static Frequency Allocation (SFA) to Dynamic Spectrum Access (DSA). The change will make efficient use of spectrum by utilizing the unused parts in different times, frequencies and spaces. With this regard, cognitive radio

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Al-Hraishawi, Hayder Abed Hussein. "DESIGN AND ANALYSIS OF COGNITIVE MASSIVE MIMO NETWORKS WITH UNDERLAY SPECTRUM SHARING." OpenSIUC, 2017. https://opensiuc.lib.siu.edu/dissertations/1412.

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Recently, massive multiple-input multiple-output (MIMO) systems have gained significant attention as a new network architecture to not only achieving unprecedented spectral and energy efficiencies, but also to alleviating propagation losses and inter-user/inter-cell interference. Therefore, massive MIMO has been identified as one of the key candidate technologies for the 5th generation wireless standard. This dissertation thus focuses on (1) developing a performance analysis framework for cognitive massive MIMO systems by investigating the uplink transmissions of multi-cell multi-user massiv

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Kumar, Bhupendra. "Performance of an underlay cooperative cognitive networks with a buffer-aided-relay." Thesis, IIT, Delhi, 2019. http://eprint.iitd.ac.in:80//handle/2074/8070.

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Kabiri, Charles. "On the Performance of Underlay Cognitive Radio Networks with Interference Constraints and Relaying." Doctoral thesis, Blekinge Tekniska Högskola [bth.se], Faculty of Computing - Department of Communication Systems, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00609.

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Efficiently allocating the scarce and expensive radio resources is a key challenge for advanced radio communication systems. To this end, cognitive radio (CR) has emerged as a promising solution which can offer considerable improvements in spectrum utilization. Furthermore, cooperative communication is a concept proposed to obtain spatial diversity gains through relays without requiring multiple antennas. To benefit from both CR and cooperative communications, a combination of CR networks (CRNs) with cooperative relaying referred to as cognitive cooperative relay networks (CCRNs) has recently

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Tran, Hung. "Performance Analysis of Cognitive Radio Networks with Interference Constraints." Doctoral thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00550.

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To support the rapidly increasing number of mobile users and mobile multimedia services, and the related demands for bandwidth, wireless communication technology is facing a potentially scarcity of radio spectrum resources. However, spectrum measurement campaigns have shown that the shortage of radio spectrum is due to inefficient usage and inflexible spectrum allocation policies. Thus, to be able to meet the requirements of bandwidth and spectrum utilization, spectrum underlay access, one of the techniques in cognitive radio networks (CRNs), has been proposed as a frontier solution to deal wi

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Sibomana, Louis. "Performance Analysis of Cognitive Radio Networks under Spectrum Sharing and Security Constraints." Doctoral thesis, Blekinge Tekniska Högskola, Institutionen för kommunikationssystem, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-11739.

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The cognitive radio network (CRN) concept has been proposed as a solution to the growing demand and underutilization of the radio spectrum. To improve the radio spectrum utilization, CRN technology allows the coexistence of licensed and unlicensed systems over the same spectrum. In an underlay spectrum sharing system, secondary users (SUs) transmit simultaneously with the primary users (PUs) in the same frequency band given that the interference caused by the SU to the PU remains below a tolerable interference limit. Besides the transmission power limitation, a secondary network is subject to

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Chu, Thi My Chinh. "On the Performance Assessment of Advanced Cognitive Radio Networks." Doctoral thesis, Blekinge Tekniska Högskola [bth.se], Faculty of Computing - Department of Communication Systems, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00611.

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Due to the rapid development of wireless communications together with the inflexibility of the current spectrum allocation policy, radio spectrum becomes more and more exhausted. One of the critical challenges of wireless communication systems is to efficiently utilize the limited frequency resources to be able to support the growing demand of high data rate wireless services. As a promising solution, cognitive radios have been suggested to deal with the scarcity and under-utilization of radio spectrum. The basic idea behind cognitive radios is to allow unlicensed users, also called secondary

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Devanarayana, Chamara. "Spectrum access in cognitive radio networks based on prediction and estimation." EURASIP Journal on Wireless Communications and Networking, 2011. http://hdl.handle.net/1993/31605.

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In the literature, Cognitive radio (CR) as well as full-duplex (FD) communication technologies are proposed to increase the spectrum efficiency. The main contribution of this thesis is to introduce prediction and estimation techniques with low control overhead, and use the predicted or estimated information in resource allocation in CR networks, both in the overlay networks and the underlay networks. Prediction and estimation are important in increasing the data rate and keeping the interference at a low level. In the overlay scheme, I modeled the primary user (PU) traffic characteristi

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Samarasekera, Andawattage Chaminda Janaka. "The Performance of Dual-Hop Decode-and-Forward Underlay Cognitive Relay Networks with Interference Power Constraints over Weibull Fading Channels." Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3201.

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With the rapid development and the increasing use of wireless devices, spectrum scarcity has become a problem. The higher frequencies have bad propagation characteristics and the lower frequencies have low data rates, therefore the radio spectrum that is available for efficient wireless transmission is a limited resource. One of the proposed solutions for this problem is cognitive relay networks (CRNs), where cognitive radio is combined with a cooperative spectrum sharing system to increase the spectrum utilization. In this thesis, the outage probability performances of underlay CRNs with inte

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Book chapters on the topic "Networks with underlay cognitive nodes"

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Deka, Sanjib K., and Nityanada Sarma. "Channel-Usage Model in Underlay Cognitive Radio Networks." In Lecture Notes in Electrical Engineering. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6154-8_12.

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Ngoc, Pham Thi Dan, Thi-Tuyet-Hai Nguyen, Tan N. Nguyen, and Lam-Thanh Tu. "Performance Analysis of Cognitive Underlay NOMA Random Networks Under Nakagami-m Channel." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-65656-9_35.

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Mei, Yanan, Yanhui Lu, Xiaomin Mu, and Xin Liu. "Distributed Fast Convergent Power Allocation Algorithm in Underlay Cognitive Radio Networks." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30493-4_34.

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Kim, Su Min, and Junsu Kim. "Buffer-Aided Relay Selection with Primary Sensing in Underlay Cognitive Radio Networks." In Lecture Notes in Electrical Engineering. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-1536-6_42.

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ElShaarany, Ahmed M., Mohamed M. Abdallah, Salama Ikki, Mohamed M. Khairy, and Khalid Qaraqe. "Best Relay Selection for DF Underlay Cognitive Networks with Different Modulation Levels." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24540-9_23.

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Rawat, Danda B., Min Song, and Sachin Shetty. "Resource Allocation in Spectrum Underlay Cognitive Radio Networks." In Dynamic Spectrum Access for Wireless Networks. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15299-8_2.

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Karim, Hezerul Abdul, Hafizal Mohamad, Nordin Ramli, and Aduwati Sali. "Multiple Description Video Coding for Underlay Cognitive Radio Network." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24540-9_53.

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He, Xiaoli, Hong Jiang, Yu Song, and He Xiao. "Optimal Resource Allocation for Underlay Cognitive Radio Networks." In Cloud Computing and Security. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00015-8_31.

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Jia, Jian, Ting Jiang, Wei Guo, and Xiaoying Qiu. "Physical Layer Security of a Buffer-Aided Relay Selection for Underlay Cognitive Radio Network." In Lecture Notes in Electrical Engineering. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6508-9_121.

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Han, Hui, Xiang Chen, and Yun Lin. "Novel Cognitive Radio Network Setup Mechanism Using Underlay as Control Channel to Enhance Efficiency." In Lecture Notes in Electrical Engineering. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-6571-2_8.

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Conference papers on the topic "Networks with underlay cognitive nodes"

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Fan, Hongbin, Weiwei Yang, Wenqiang Feng, and Chuanzhen Rong. "Relay Assisted Covert Communications in Underlay Cognitive Radio Networks." In 2024 International Conference on Ubiquitous Communication (Ucom). IEEE, 2024. http://dx.doi.org/10.1109/ucom62433.2024.10695839.

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Dhungana, Yamuna, and Chintha Tellambura. "Outage probability of underlay cognitive relay networks with spatially random nodes." In GLOBECOM 2014 - 2014 IEEE Global Communications Conference. IEEE, 2014. http://dx.doi.org/10.1109/glocom.2014.7037366.

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Chen, Dan, Hong Ji, and Xi Li. "Distributed best-relay node selection in underlay cognitive radio networks: A restless bandits approach." In 2011 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2011. http://dx.doi.org/10.1109/wcnc.2011.5779303.

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Jeong, Youngmin, Tony Q. S. Quek, and Hyundong Shin. "Downlink beamforming optimization for cognitive underlay networks." In Its Applications (Isita2010). IEEE, 2010. http://dx.doi.org/10.1109/isita.2010.5649545.

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Seyfi, Mehdi, Sami Muhaidat, and Jie Liang. "Relay selection in underlay cognitive radio networks." In 2012 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2012. http://dx.doi.org/10.1109/wcnc.2012.6214285.

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Kaushik, Ankit, Ralph Tanbourgi, and Friedrich Jondral. "Operating characteristics of underlay cognitive relay networks." In 2014 IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC). IEEE, 2014. http://dx.doi.org/10.1109/pimrc.2014.7136351.

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Chakravarthy, Vasu, Zhiqiang Wu, Michael Temple, Fred Garber, and Xue Li. "Cognitive Radio Centric Overlay/Underlay Waveform." In 2008 IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN). IEEE, 2008. http://dx.doi.org/10.1109/dyspan.2008.20.

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Tourki, Kamel, Khalid A. Qaraqe, and Mohamed-Slim Alouini. "Outage analysis for underlay relay-assisted cognitive networks." In GLOBECOM 2012 - 2012 IEEE Global Communications Conference. IEEE, 2012. http://dx.doi.org/10.1109/glocom.2012.6503284.

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Lameiro, Christian, Ignacio Santamaria, Wolfgang Utschiclk, and Peter J. Schreier. "Maximally improper interference in underlay cognitive radio networks." In 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2016. http://dx.doi.org/10.1109/icassp.2016.7472361.

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Marques, Antonio G., Sergio Molinero, and Georgios B. Giannakis. "Underlay multi-hop cognitive networks with orthogonal access." In 2015 IEEE 16th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM). IEEE, 2015. http://dx.doi.org/10.1109/wowmom.2015.7158197.

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