Academic literature on the topic 'Future Cellular and IoT Networks'
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Journal articles on the topic "Future Cellular and IoT Networks":
Vishnubhatla, Arvind. "Cellular IOT using nRF9160kit." International Journal of Online and Biomedical Engineering (iJOE) 16, no. 15 (December 15, 2020): 34. http://dx.doi.org/10.3991/ijoe.v16i15.18987.
Pan, Shin-Hung, and Shu-Ching Wang. "Optimal Consensus with Dual Abnormality Mode of Cellular IoT Based on Edge Computing." Sensors 21, no. 2 (January 19, 2021): 671. http://dx.doi.org/10.3390/s21020671.
Ahmed Osman, Radwa, and Amira I. Zaki. "Energy-Efficient and Reliable Internet of Things for 5G: A Framework for Interference Control." Electronics 9, no. 12 (December 17, 2020): 2165. http://dx.doi.org/10.3390/electronics9122165.
Kadus, Shubhangi G., and Sagar S. Wabale. "Revolution in IoT with 5G Network." International Journal for Research in Applied Science and Engineering Technology 11, no. 3 (March 31, 2023): 178–82. http://dx.doi.org/10.22214/ijraset.2023.49297.
Abanga, Ellen Akongwin. "A Review of Internet of Things (IoT) and Security Concerns." Advances in Multidisciplinary and scientific Research Journal Publication 10, no. 4 (December 30, 2022): 121–30. http://dx.doi.org/10.22624/aims/digital/v10n4p13.
Nikhat Akhtar and Yusuf Perwej. "The internet of nano things (IoNT) existing state and future Prospects." GSC Advanced Research and Reviews 5, no. 2 (November 30, 2020): 131–50. http://dx.doi.org/10.30574/gscarr.2020.5.2.0110.
Zikria, Yousaf, Sung Kim, Muhammad Afzal, Haoxiang Wang, and Mubashir Rehmani. "5G Mobile Services and Scenarios: Challenges and Solutions." Sustainability 10, no. 10 (October 11, 2018): 3626. http://dx.doi.org/10.3390/su10103626.
Andrabi, Umer Mukhtar, Sergey N. Stepanov, Juvent Ndayikunda, and Margarita G. Kanishcheva. "CELLULAR NETWORK RESOURCE DISTRIBUTION METHODS FOR THE JOINT SERVICING OF REAL-TIME MULTISERVICE TRAFFIC AND GROUPED IOT TRAFFIC." T-Comm 14, no. 10 (2020): 61–69. http://dx.doi.org/10.36724/2072-8735-2020-14-10-61-69.
Nagah, Mohamed, Shimaa Mahmoud, Mohamed Megahed, and 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.
Tikhvinskiy, Valery, Grigory Bochechka, Andrey Gryazev, and Altay Aitmagambetov. "Comparative Analysis of QoS Management and Technical Requirements in 3GPP Standards for Cellular IoT Technologies." Journal of Telecommunications and Information Technology 2 (June 29, 2018): 41–47. http://dx.doi.org/10.26636/jtit.2018.122717.
Dissertations / Theses on the topic "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.
The 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/.
Imran, Ali. "Self organization in future cellular networks." Thesis, University of Surrey, 2011. http://epubs.surrey.ac.uk/842776/.
Akbari, Iman. "Enabling self organisation for future cellular networks." Thesis, University of Surrey, 2018. http://epubs.surrey.ac.uk/849661/.
Koshi, Virtyt. "Radio planning for future mobile communication networks." Thesis, University of Oxford, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.390488.
Larue, 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.
Wireless 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.
Rasheduzzaman, Mirza. "Contributing towards improved communication systems for future cellular networks." Thesis, University of Sheffield, 2017. http://etheses.whiterose.ac.uk/17686/.
Hossain, 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.
QC 20170928
Iscar, Vergara Jorge. "Channel and Noise Variance Estimation for Future 5G Cellular Networks." FIU Digital Commons, 2016. http://digitalcommons.fiu.edu/etd/3026.
Books on the topic "Future Cellular and IoT Networks":
Andrea, Cabibbo, Grant Richard P, and Helmer-Citterich Manuela, eds. The Internet for cell and molecular biologists: Current applications and future potential. Wymondham: Horizon Scientific, 2002.
Pötsch, Thomas. Future Mobile Transport Protocols: Adaptive Congestion Control for Unpredictable Cellular Networks. Springer Vieweg, 2016.
Pötsch, Thomas. Future Mobile Transport Protocols: Adaptive Congestion Control for Unpredictable Cellular Networks. Springer Vieweg. in Springer Fachmedien Wiesbaden GmbH, 2016.
Zorumski, Charles, and Eugene Rubin. Psychiatry and Clinical Neuroscience. Oxford University Press, 2012. http://dx.doi.org/10.1093/med/9780199768769.001.1.
Madhu, G., Sandeep Kautish, A. Govardhan, and Avinash Sharma, eds. 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.
Sulaiman, Noor Suhana, Akhyari Nasir, Azliza Yacob, Mohd Alif Hasmani Abd Ghani, Mohd Tamizan Abu Bakar, Lukmanulhakim Ngah, Siti Norwahidayah Wahab, Mohd Shah Shafie Idris, and Mohd Azizuddin Ali. FUNDAMENTAL OF NETWORKING. 2024th ed. PENERBIT UNIVERSITI MALAYSIA PERLIS, 2024. http://dx.doi.org/10.58915/bk2023.018.
Book chapters on the topic "Future Cellular and IoT Networks":
Bahalul Haque, A. K. M., Tasfia Nausheen, Abdullah Al Mahfuj Shaan, and 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.
Kaur, Upinder, and 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.
Das, Anwesha, Aninda Chowdhury, and 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.
Sari, Alparslan, Alexios Lekidis, and 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.
Govindan, Kannan, Deepthi Chander, Bhushan G. Jagyasi, Shabbir N. Merchant, and 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.
Bruno, Emmanuel, Romane Gallier, and 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.
Gabillon, Alban, and 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.
Phalaagae, Pendukeni, Adamu Murtala Zungeru, Boyce Sigweni, Joseph M. Chuma, and 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.
Song, Wei, and 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.
Can, 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.
Conference papers on the topic "Future Cellular and IoT Networks":
Ballal, Kalpit Dilip, Radheshyam Singh, Lars Dittmann, and 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.
Karapantelakis, Athanasios, Hongxin Liang, Keven Wang, Konstantinos Vandikas, Rafia Inam, Elena Fersman, Ignacio Mulas-Viela, Nicolas Seyvet, and 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.
Malarski, Krzysztof Mateusz, Kalpit Dilip Ballal, and 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.
Jing An, Zhichen Wang, and 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.
Soos, Gabor, Daniel Kozma, Ferenc Nandor Janky, and 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.
Bharathi, S., and 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.
Xu, Liangchun, and 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.
Singh, Boby, Nikita Singh, Akash Kaushish, and 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.
Arslan, Serhat, Ali Abedi, and 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.
Harsanyi, Karoly, Attila Kiss, and 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.