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Artykuły w czasopismach na temat "Networks with underlay cognitive nodes"
Hussain, Syed Imtiaz, Mohamed M. Abdallah, Mohamed-Slim Alouini, Khalid Qaraqe i Mazen Hasna. "Relay selection in underlay cognitive networks with fixed transmission power nodes". Transactions on Emerging Telecommunications Technologies 24, nr 7-8 (31.07.2013): 734–47. http://dx.doi.org/10.1002/ett.2691.
Pełny tekst źródłaAlhamad, Raed, i Hatem Boujemaa. "Intelligent Reflecting Surfaces with Adaptive Transmit Power for Underlay Cognitive Radio Networks". Wireless Communications and Mobile Computing 2022 (17.08.2022): 1–7. http://dx.doi.org/10.1155/2022/2787466.
Pełny tekst źródłaToan, Hoang Van, i 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, nr 1 (31.03.2017): 29. http://dx.doi.org/10.31130/jst.2017.35.
Pełny tekst źródłaKozić, Nadica, Vesna Blagojević, Aleksandra Cvetković i Predrag Ivaniš. "Performance Analysis of Wirelessly Powered Cognitive Radio Network with Statistical CSI and Random Mobility". Sensors 23, nr 9 (6.05.2023): 4518. http://dx.doi.org/10.3390/s23094518.
Pełny tekst źródłaGiang, Nguyen Hong, Vo Nguyen Quoc Bao i Hung Nguyen-Le. "Effect of CSI Imperfection on Cognitive Underlay Transmission over Nakagami-m Fading Channel". Journal of Science and Technology: Issue on Information and Communications Technology 1 (31.08.2015): 59. http://dx.doi.org/10.31130/jst.2015.13.
Pełny tekst źródłaHan, Xu, Lei Xue, Ying Xu i 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, nr 8 (15.04.2020): 2245. http://dx.doi.org/10.3390/s20082245.
Pełny tekst źródłaRaj, K. Shashi. "Interference resilient stochastic prediction based dynamic resource allocation model for cognitive MANETs". Indian Journal of Science and Technology 13, nr 41 (10.10.2020): 4332–50. http://dx.doi.org/10.17485/ijst/v13i41.687.
Pełny tekst źródłaBakht, Khush, Furqan Jameel, Zain Ali, Wali Ullah Khan, Imran Khan, Guftaar Ahmad Sardar Sidhu i Jeong Woo Lee. "Power Allocation and User Assignment Scheme for beyond 5G Heterogeneous Networks". Wireless Communications and Mobile Computing 2019 (16.11.2019): 1–11. http://dx.doi.org/10.1155/2019/2472783.
Pełny tekst źródłaTran Tin, Phu, Dang The Hung, Tan Nguyen, Tran Duy i Miroslav Voznak. "Secrecy Performance Enhancement for Underlay Cognitive Radio Networks Employing Cooperative Multi-Hop Transmission with and without Presence of Hardware Impairments". Entropy 21, nr 2 (24.02.2019): 217. http://dx.doi.org/10.3390/e21020217.
Pełny tekst źródłaMinh Nam, Pham, Ha Duy Hung, Lam-Thanh Tu, Pham Viet Tuan, Tran Trung Duy i Tan Hanh. "Outage Performance of Interference Cancellation-Aided Two-Way Relaying Cognitive Network with Primary TAS/SC Communication and Secondary Partial Relay Selection". Electronics 11, nr 22 (8.11.2022): 3645. http://dx.doi.org/10.3390/electronics11223645.
Pełny tekst źródłaRozprawy doktorskie na temat "Networks with underlay cognitive nodes"
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.
Pełny tekst źródłaAl-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.
Pełny tekst źródłaKabiri, 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.
Pełny tekst źródłaTran, 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.
Pełny tekst źródłaSibomana, 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.
Pełny tekst źródłaChu, 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.
Pełny tekst źródłaDevanarayana, 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.
Pełny tekst źródłaOctober 2016
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.
Pełny tekst źródłaLu, Lu. "Spectral-efficient design in modern wireless communications networks". Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/53902.
Pełny tekst źródłaMoteka, Leutsoa. "User pairing and power allocation in underlay cognitive NOMA networks". Thesis, 2020. https://hdl.handle.net/10539/31115.
Pełny tekst źródłaThe unique structure of Non-Orthogonal Multiple Access (NOMA), a candidate for multiple access techniques for fifth-generation mobile networks, poses formidable design challenges when the number of users in the network rises. Fifth generation networks, however, demand hyper connected societies with phenomenal number of users. In a multi-channel NOMA system with a large number of users, the literature has shown that the best performance is achieved if no more than three users share a channel. Most research typically allocates two users to a channel. One of the key issues then is user pairing, which must be done in order to maximize the network capacity. A number of user pairing schemes have been derived in the literature, but these have been done mostly for non-cognitive radio networks. A need for user pairing schemes in cognitive networks has therefore risen. Developed schemes need to take into account a plethora of complications such as energy consumption and an increase in interference raised in the cognitive environment. The main focus of this dissertation is to mathematically model a framework to optimize power allocation and user pairing in a cognitive NOMA network. In particular, we determine various power allocation schemes that can cope with the severe energy constraints of an underlay cognitive network and employ these schemes for use indifferent user pairing schemes. First, we employ an underlay random pairing algorithm and an underlay channel state sorting pairing algorithm, for use in a large-scale network. Because of the low complexity of these algorithms, we use their performance to study and compare with other pairing algorithms. Then we propose a near-optimal preference list matching algorithm (PLMA) based on matching theory to perform user pairing. Performance evaluation of the proposed schemes is presented through simulations. Results show how that the preference list matching algorithm effectively outperforms other pairing algorithms and can also perform better that the Hungarian algorithm
CK2021
Części książek na temat "Networks with underlay cognitive nodes"
Deka, Sanjib K., i Nityanada Sarma. "Channel-Usage Model in Underlay Cognitive Radio Networks". W Lecture Notes in Electrical Engineering, 115–23. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6154-8_12.
Pełny tekst źródłaMei, Yanan, Yanhui Lu, Xiaomin Mu i Xin Liu. "Distributed Fast Convergent Power Allocation Algorithm in Underlay Cognitive Radio Networks". W Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 345–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30493-4_34.
Pełny tekst źródłaKim, Su Min, i Junsu Kim. "Buffer-Aided Relay Selection with Primary Sensing in Underlay Cognitive Radio Networks". W Lecture Notes in Electrical Engineering, 319–26. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-1536-6_42.
Pełny tekst źródłaElShaarany, Ahmed M., Mohamed M. Abdallah, Salama Ikki, Mohamed M. Khairy i Khalid Qaraqe. "Best Relay Selection for DF Underlay Cognitive Networks with Different Modulation Levels". W Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 282–94. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24540-9_23.
Pełny tekst źródłaRawat, Danda B., Min Song i Sachin Shetty. "Resource Allocation in Spectrum Underlay Cognitive Radio Networks". W Dynamic Spectrum Access for Wireless Networks, 13–24. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15299-8_2.
Pełny tekst źródłaHe, Xiaoli, Hong Jiang, Yu Song i He Xiao. "Optimal Resource Allocation for Underlay Cognitive Radio Networks". W Cloud Computing and Security, 358–71. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00015-8_31.
Pełny tekst źródłaKarim, Hezerul Abdul, Hafizal Mohamad, Nordin Ramli i Aduwati Sali. "Multiple Description Video Coding for Underlay Cognitive Radio Network". W Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 643–52. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24540-9_53.
Pełny tekst źródłaJia, Jian, Ting Jiang, Wei Guo i Xiaoying Qiu. "Physical Layer Security of a Buffer-Aided Relay Selection for Underlay Cognitive Radio Network". W Lecture Notes in Electrical Engineering, 999–1006. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6508-9_121.
Pełny tekst źródłaHan, Hui, Xiang Chen i Yun Lin. "Novel Cognitive Radio Network Setup Mechanism Using Underlay as Control Channel to Enhance Efficiency". W Lecture Notes in Electrical Engineering, 61–67. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-6571-2_8.
Pełny tekst źródłaHarounabadi, Mehdi, André Puschmann, Oleksandr Artemenko i Andreas Mitschele-Thiel. "TAG: Trajectory Aware Geographical Routing in Cognitive Radio Ad Hoc Networks with UAV Nodes". W Ad Hoc Networks, 111–22. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25067-0_9.
Pełny tekst źródłaStreszczenia konferencji na temat "Networks with underlay cognitive nodes"
Dhungana, Yamuna, i Chintha Tellambura. "Outage probability of underlay cognitive relay networks with spatially random nodes". W GLOBECOM 2014 - 2014 IEEE Global Communications Conference. IEEE, 2014. http://dx.doi.org/10.1109/glocom.2014.7037366.
Pełny tekst źródłaChen, Dan, Hong Ji i Xi Li. "Distributed best-relay node selection in underlay cognitive radio networks: A restless bandits approach". W 2011 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2011. http://dx.doi.org/10.1109/wcnc.2011.5779303.
Pełny tekst źródłaJeong, Youngmin, Tony Q. S. Quek i Hyundong Shin. "Downlink beamforming optimization for cognitive underlay networks". W Its Applications (Isita2010). IEEE, 2010. http://dx.doi.org/10.1109/isita.2010.5649545.
Pełny tekst źródłaSeyfi, Mehdi, Sami Muhaidat i Jie Liang. "Relay selection in underlay cognitive radio networks". W 2012 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2012. http://dx.doi.org/10.1109/wcnc.2012.6214285.
Pełny tekst źródłaKaushik, Ankit, Ralph Tanbourgi i Friedrich Jondral. "Operating characteristics of underlay cognitive relay networks". W 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.
Pełny tekst źródłaChakravarthy, Vasu, Zhiqiang Wu, Michael Temple, Fred Garber i Xue Li. "Cognitive Radio Centric Overlay/Underlay Waveform". W 2008 IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN). IEEE, 2008. http://dx.doi.org/10.1109/dyspan.2008.20.
Pełny tekst źródłaTourki, Kamel, Khalid A. Qaraqe i Mohamed-Slim Alouini. "Outage analysis for underlay relay-assisted cognitive networks". W GLOBECOM 2012 - 2012 IEEE Global Communications Conference. IEEE, 2012. http://dx.doi.org/10.1109/glocom.2012.6503284.
Pełny tekst źródłaLameiro, Christian, Ignacio Santamaria, Wolfgang Utschiclk i Peter J. Schreier. "Maximally improper interference in underlay cognitive radio networks". W 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2016. http://dx.doi.org/10.1109/icassp.2016.7472361.
Pełny tekst źródłaMarques, Antonio G., Sergio Molinero i Georgios B. Giannakis. "Underlay multi-hop cognitive networks with orthogonal access". W 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.
Pełny tekst źródłaTanab, Manal El, Yasmine Fahmy i Mohamed M. Khairy. "Opportunistic splitting algorithm for underlay cognitive radio networks". W 2014 Sixth International Conference on Ubiquitous and Future Networks (ICUFN). IEEE, 2014. http://dx.doi.org/10.1109/icufn.2014.6876738.
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