Auswahl der wissenschaftlichen Literatur zum Thema „Future Cellular and IoT Networks“
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Zeitschriftenartikel zum Thema "Future Cellular and IoT Networks"
Vishnubhatla, Arvind. „Cellular IOT using nRF9160kit“. International Journal of Online and Biomedical Engineering (iJOE) 16, Nr. 15 (15.12.2020): 34. http://dx.doi.org/10.3991/ijoe.v16i15.18987.
Der volle Inhalt der QuellePan, Shin-Hung, und Shu-Ching Wang. „Optimal Consensus with Dual Abnormality Mode of Cellular IoT Based on Edge Computing“. Sensors 21, Nr. 2 (19.01.2021): 671. http://dx.doi.org/10.3390/s21020671.
Der volle Inhalt der QuelleAhmed Osman, Radwa, und Amira I. Zaki. „Energy-Efficient and Reliable Internet of Things for 5G: A Framework for Interference Control“. Electronics 9, Nr. 12 (17.12.2020): 2165. http://dx.doi.org/10.3390/electronics9122165.
Der volle Inhalt der QuelleKadus, Shubhangi G., und Sagar S. Wabale. „Revolution in IoT with 5G Network“. International Journal for Research in Applied Science and Engineering Technology 11, Nr. 3 (31.03.2023): 178–82. http://dx.doi.org/10.22214/ijraset.2023.49297.
Der volle Inhalt der QuelleAbanga, Ellen Akongwin. „A Review of Internet of Things (IoT) and Security Concerns“. Advances in Multidisciplinary and scientific Research Journal Publication 10, Nr. 4 (30.12.2022): 121–30. http://dx.doi.org/10.22624/aims/digital/v10n4p13.
Der volle Inhalt der QuelleNikhat Akhtar und Yusuf Perwej. „The internet of nano things (IoNT) existing state and future Prospects“. GSC Advanced Research and Reviews 5, Nr. 2 (30.11.2020): 131–50. http://dx.doi.org/10.30574/gscarr.2020.5.2.0110.
Der volle Inhalt der QuelleZikria, Yousaf, Sung Kim, Muhammad Afzal, Haoxiang Wang und Mubashir Rehmani. „5G Mobile Services and Scenarios: Challenges and Solutions“. Sustainability 10, Nr. 10 (11.10.2018): 3626. http://dx.doi.org/10.3390/su10103626.
Der volle Inhalt der QuelleAndrabi, Umer Mukhtar, Sergey N. Stepanov, Juvent Ndayikunda und Margarita G. Kanishcheva. „CELLULAR NETWORK RESOURCE DISTRIBUTION METHODS FOR THE JOINT SERVICING OF REAL-TIME MULTISERVICE TRAFFIC AND GROUPED IOT TRAFFIC“. T-Comm 14, Nr. 10 (2020): 61–69. http://dx.doi.org/10.36724/2072-8735-2020-14-10-61-69.
Der volle Inhalt der QuelleNagah, Mohamed, Shimaa Mahmoud, Mohamed Megahed und Mohammed Salama. „Exploring the Applications of 5G Mobile Communication Networks: A Comprehensive Tutorial“. International Uni-Scientific Research Journal 4 (2023): 9–14. http://dx.doi.org/10.59271/s44839.023.2206.2.
Der volle Inhalt der QuelleTikhvinskiy, Valery, Grigory Bochechka, Andrey Gryazev und Altay Aitmagambetov. „Comparative Analysis of QoS Management and Technical Requirements in 3GPP Standards for Cellular IoT Technologies“. Journal of Telecommunications and Information Technology 2 (29.06.2018): 41–47. http://dx.doi.org/10.26636/jtit.2018.122717.
Der volle Inhalt der QuelleDissertationen zum Thema "Future Cellular and IoT Networks"
Djemai, Ibrahim. „Joint offloading-scheduling policies for future generation wireless networks“. Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAS007.
Der volle Inhalt der QuelleThe challenges posed by the increasing number of connected devices, high energy consumption, and environmental impact in today's and future wireless networks are gaining more attention. New technologies like Mobile Edge Computing (MEC) have emerged to bring cloud services closer to the devices and address their computation limitations. Enabling these devices and the network nodes with Energy Harvesting (EH) capabilities is also promising to allow for consuming energy from sustainable and environmentally friendly sources. In addition, Non-Orthogonal Multiple Access (NOMA) is a pivotal technique to achieve enhanced mobile broadband. Aided by the advancement of Artificial Intelligence, especially Reinforcement Learning (RL) models, the thesis work revolves around devising policies that jointly optimize scheduling and computational offloading for devices with EH capabilities, NOMA-enabled communications, and MEC access. Moreover, when the number of devices increases and so does the system complexity, NOMA clustering is performed and Federated Learning is used to produce RL policies in a distributed way. The thesis results validate the performance of the proposed RL-based policies, as well as the interest of using NOMA technique
Yi, Na. „Cooperative communication for future cellular networks“. Thesis, University of Surrey, 2009. http://epubs.surrey.ac.uk/843080/.
Der volle Inhalt der QuelleImran, Ali. „Self organization in future cellular networks“. Thesis, University of Surrey, 2011. http://epubs.surrey.ac.uk/842776/.
Der volle Inhalt der QuelleAkbari, Iman. „Enabling self organisation for future cellular networks“. Thesis, University of Surrey, 2018. http://epubs.surrey.ac.uk/849661/.
Der volle Inhalt der QuelleKoshi, Virtyt. „Radio planning for future mobile communication networks“. Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.390488.
Der volle Inhalt der QuelleLarue, Guillaume. „AI models for digital signal processing in future 6G-IoT networks“. Electronic Thesis or Diss., Institut polytechnique de Paris, 2023. http://www.theses.fr/2023IPPAT003.
Der volle Inhalt der QuelleWireless technologies are of paramount importance to today's societies and future 6th generation communication networks are expected to address many societal and technological challenges. While communications infrastructures have a growing environmental impact that needs to be reduced, digital technologies also have a role to play in reducing the impact of all sectors of the economy. To this end, the future networks will not only have to enable more efficient information transfer, but also meet the growing need for data exchange capacity. This is particularly the role of the Internet of Things use cases, where a massive number of sensors allow to monitor complex systems. These use cases are associated with many constraints such as limited energy resources and complexity. Therefore, an efficient and low-complexity physical layer - responsible for the transmission of information between the network nodes - is absolutely crucial. In this regard, the use of artificial intelligence techniques is relevant. On the one hand, the mathematical framework of neural networks allows for efficient and low-cost generic hardware implementations. On the other hand, the application of learning procedures can improve the performance of certain algorithms. In this work, we are interested in the use of neural networks and machine learning for digital signal processing in the context of 6G-IoT networks. First, we are interested in the transcription of certain equalisation, demodulation and decoding algorithms from the digital communications literature into neural networks. Secondly, we are interested in the application of learning mechanisms on these neural network structures in order to improve their performance. A linear block decoder is proposed which allows the blind discovery of a decoding scheme whose performance is at least equivalent to that of the reference decoder. Finally, an end-to-end structure is presented, allowing joint learning of an encoding/decoding scheme with performance and complexity comparable to state-of-the-art solutions
Aquilina, Paula. „Advanced interference management techniques for future generation cellular networks“. Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/28714.
Der volle Inhalt der QuelleRasheduzzaman, Mirza. „Contributing towards improved communication systems for future cellular networks“. Thesis, University of Sheffield, 2017. http://etheses.whiterose.ac.uk/17686/.
Der volle Inhalt der QuelleHossain, Mohammad Istiak. „Designing Efficient Access Control to Comply Massive-Multiservice IoT over Cellular Networks“. Licentiate thesis, KTH, Radio Systems Laboratory (RS Lab), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-214974.
Der volle Inhalt der QuelleQC 20170928
Iscar, Vergara Jorge. „Channel and Noise Variance Estimation for Future 5G Cellular Networks“. FIU Digital Commons, 2016. http://digitalcommons.fiu.edu/etd/3026.
Der volle Inhalt der QuelleBücher zum Thema "Future Cellular and IoT Networks"
Andrea, Cabibbo, Grant Richard P und Helmer-Citterich Manuela, Hrsg. The Internet for cell and molecular biologists: Current applications and future potential. Wymondham: Horizon Scientific, 2002.
Den vollen Inhalt der Quelle findenPötsch, Thomas. Future Mobile Transport Protocols: Adaptive Congestion Control for Unpredictable Cellular Networks. Springer Vieweg, 2016.
Den vollen Inhalt der Quelle findenPötsch, Thomas. Future Mobile Transport Protocols: Adaptive Congestion Control for Unpredictable Cellular Networks. Springer Vieweg. in Springer Fachmedien Wiesbaden GmbH, 2016.
Den vollen Inhalt der Quelle findenZorumski, Charles, und Eugene Rubin. Psychiatry and Clinical Neuroscience. Oxford University Press, 2012. http://dx.doi.org/10.1093/med/9780199768769.001.1.
Der volle Inhalt der QuelleMadhu, G., Sandeep Kautish, A. Govardhan und Avinash Sharma, Hrsg. Emerging Computational Approaches in Telehealth and Telemedicine: A Look at The Post-COVID-19 Landscape. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/97898150792721220101.
Der volle Inhalt der QuelleSulaiman, Noor Suhana, Akhyari Nasir, Azliza Yacob, Mohd Alif Hasmani Abd Ghani, Mohd Tamizan Abu Bakar, Lukmanulhakim Ngah, Siti Norwahidayah Wahab, Mohd Shah Shafie Idris und Mohd Azizuddin Ali. FUNDAMENTAL OF NETWORKING. 2024. Aufl. PENERBIT UNIVERSITI MALAYSIA PERLIS, 2024. http://dx.doi.org/10.58915/bk2023.018.
Der volle Inhalt der QuelleBuchteile zum Thema "Future Cellular and IoT Networks"
Bahalul Haque, A. K. M., Tasfia Nausheen, Abdullah Al Mahfuj Shaan und Saydul Akbar Murad. „Security Attacks and Countermeasures in 5G Enabled Internet of Things“. In 5G and Beyond, 127–49. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3668-7_7.
Der volle Inhalt der QuelleKaur, Upinder, und Shalu. „Blockchain- and Deep Learning-Empowered Resource Optimization in Future Cellular Networks, Edge Computing, and IoT: Open Challenges and Current Solutions“. In Blockchain for 5G-Enabled IoT, 441–74. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67490-8_17.
Der volle Inhalt der QuelleDas, Anwesha, Aninda Chowdhury und Riya Sil. „Third Industrial Revolution: 5G Wireless Systems, Internet of Things, and Beyond“. In 5G and Beyond, 19–43. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3668-7_2.
Der volle Inhalt der QuelleSari, Alparslan, Alexios Lekidis und Ismail Butun. „Industrial Networks and IIoT: Now and Future Trends“. In Industrial IoT, 3–55. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42500-5_1.
Der volle Inhalt der QuelleGovindan, Kannan, Deepthi Chander, Bhushan G. Jagyasi, Shabbir N. Merchant und Uday B. Desai. „Cellular Networks: Past, Present and Future“. In Multihop Mobile Wireless Networks, 43–50. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003357162-5.
Der volle Inhalt der QuelleBruno, Emmanuel, Romane Gallier und Alban Gabillon. „Enforcing Access Controls in IoT Networks“. In Future Data and Security Engineering, 429–45. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-35653-8_29.
Der volle Inhalt der QuelleGabillon, Alban, und Emmanuel Bruno. „A Security Model for IoT Networks“. In Future Data and Security Engineering, 39–56. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03192-3_4.
Der volle Inhalt der QuellePhalaagae, Pendukeni, Adamu Murtala Zungeru, Boyce Sigweni, Joseph M. Chuma und Thabo Semong. „Future Challenges of IoT Sensor Networks“. In Green Internet of Things Sensor Networks, 119–22. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54983-1_7.
Der volle Inhalt der QuelleSong, Wei, und Weihua Zhuang. „Conclusions and Future Directions“. In Interworking of Wireless LANs and Cellular Networks, 61–63. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-4379-7_5.
Der volle Inhalt der QuelleCan, Başak. „Conclusions and Future Work“. In Link Adaptation for Relay-Based Cellular Networks, 137–40. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003338765-7.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Future Cellular and IoT Networks"
Ballal, Kalpit Dilip, Radheshyam Singh, Lars Dittmann und Sarah Ruepp. „Experimental Evaluation of Roaming Performance of Cellular IoT Networks“. In 2022 Thirteenth International Conference on Ubiquitous and Future Networks (ICUFN). IEEE, 2022. http://dx.doi.org/10.1109/icufn55119.2022.9829590.
Der volle Inhalt der QuelleKarapantelakis, Athanasios, Hongxin Liang, Keven Wang, Konstantinos Vandikas, Rafia Inam, Elena Fersman, Ignacio Mulas-Viela, Nicolas Seyvet und Vasileios Giannokostas. „DevOps for IoT Applications Using Cellular Networks and Cloud“. In 2016 IEEE 4th International Conference on Future Internet of Things and Cloud (FiCloud). IEEE, 2016. http://dx.doi.org/10.1109/ficloud.2016.55.
Der volle Inhalt der QuelleMalarski, Krzysztof Mateusz, Kalpit Dilip Ballal und Sarah Ruepp. „D2D-enabled Failure-tolerance in Cellular IoT“. In 2021 12th International Conference on Network of the Future (NoF). IEEE, 2021. http://dx.doi.org/10.1109/nof52522.2021.9609924.
Der volle Inhalt der QuelleJing An, Zhichen Wang und Hongyu Wang. „A novel grouping algorithm for future cellular networks“. In 2010 IEEE Youth Conference on Information, Computing and Telecommunications (YC-ICT). IEEE, 2010. http://dx.doi.org/10.1109/ycict.2010.5713114.
Der volle Inhalt der QuelleSoos, Gabor, Daniel Kozma, Ferenc Nandor Janky und Pal Varga. „IoT Device Lifecycle – A Generic Model and a Use Case for Cellular Mobile Networks“. In 2018 IEEE 6th International Conference on Future Internet of Things and Cloud (FiCloud). IEEE, 2018. http://dx.doi.org/10.1109/ficloud.2018.00033.
Der volle Inhalt der QuelleBharathi, S., und P. Durgadevi. „An Intensive Investigation of Vehicular Adhoc Network Simulators“. In International Research Conference on IOT, Cloud and Data Science. Switzerland: Trans Tech Publications Ltd, 2023. http://dx.doi.org/10.4028/p-715gbh.
Der volle Inhalt der QuelleXu, Liangchun, und Jason Rife. „Doppler-aided Line-of-sight Identification and Localization in Future Cellular Networks“. In 31st International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2018). Institute of Navigation, 2018. http://dx.doi.org/10.33012/2018.15908.
Der volle Inhalt der QuelleSingh, Boby, Nikita Singh, Akash Kaushish und Neha Gupta. „Optimizing IOT Drones using Cellular Networks“. In 2020 12th International Conference on Computational Intelligence and Communication Networks (CICN). IEEE, 2020. http://dx.doi.org/10.1109/cicn49253.2020.9242594.
Der volle Inhalt der QuelleArslan, Serhat, Ali Abedi und Sachin Katti. „d-Cellular: Trust-Free Connectivity in Decentralized Cellular Networks“. In 2023 IEEE Future Networks World Forum (FNWF). IEEE, 2023. http://dx.doi.org/10.1109/fnwf58287.2023.10520508.
Der volle Inhalt der QuelleHarsanyi, Karoly, Attila Kiss und Tamas Sziranyi. „Wormhole detection in wireless sensor networks using spanning trees“. In 2018 IEEE International Conference on Future IoT Technologies (Future IoT). IEEE, 2018. http://dx.doi.org/10.1109/fiot.2018.8325596.
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