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Gotowe bibliografie tematyczne / 3rd generation wireless networks / Artykuły w czasopismach

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Artykuły w czasopismach na temat „3rd generation wireless networks”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 1 lutego 2022

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1

Geng-Sheng Kuo, A. Mishra, and R. Prasad. "QoS and resource allocation in the 3rd-generation wireless networks [Guest Editorial]." IEEE Communications Magazine 39, no. 2 (February 2001): 115. http://dx.doi.org/10.1109/mcom.2001.900639.

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Marzook, Ali, Hayder Mohammed, and Hisham Roomi. "Performance of Non-Orthogonal Multiple Access (NOMA) with Successive Interference Cancellation (SIC)." 3D SCEEER Conference sceeer, no. 3d (July 1, 2020): 152–56. http://dx.doi.org/10.37917/ijeee.sceeer.3rd.21.

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Non-Orthogonal Multiple Access (NOMA) has been promised for fifth generation (5G) cellular wireless network that can serve multiple users at same radio resources time, frequency, and code domains with different power levels. In this paper, we present a new simulation compression between a random location of multiple users for Non-Orthogonal Multiple Access (NOMA) and Orthogonal Multiple Access (OMA) that depend on Successive Interference Cancellation (SIC) and generalized the suggested joint user pairing for NOMA and beyond cellular networks. Cell throughput and Energy Efficiency (EE) are gain

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3

Kang, Yoohwa, Changki Kim, Donghyeok An, and Hyunsoo Yoon. "Multipath transmission control protocol–based multi-access traffic steering solution for 5G multimedia-centric network: Design and testbed system implementation." International Journal of Distributed Sensor Networks 16, no. 2 (February 2020): 155014772090975. http://dx.doi.org/10.1177/1550147720909759.

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Various technologies have been developed for the efficient use of the multiple radio access technologies resource at the radio access network level or other network levels to improve user service quality in mobile communication networks. In long-term evolution, mobile carriers are commercializing radio access network-level traffic aggregation technologies such as licensed-assisted access-long-term evolution, long-term evolution-unlicensed, and long-term evolution-wireless local area network aggregation, which use the multi-accesses of the 3rd Generation Partnership Project and WiFi, and the mu

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4

XYNOGALAS, STAVROS, IOANNA ROUSSAKI, MARIA CHANTZARA, and MILTIADES ANAGNOSTOU. "CONTEXT MANAGEMENT IN VIRTUAL HOME ENVIRONMENT SYSTEMS." Journal of Circuits, Systems and Computers 13, no. 02 (April 2004): 293–311. http://dx.doi.org/10.1142/s021812660400143x.

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The emerging 3rd generation services are provided through various types of networks and terminals. Roaming users rely on new kinds of wireless networks and terminals to offer mobility and make services available everywhere. The users' requirement for continuous access to personalized services from any place, transparently and independently of the underlying network technology and the terminal or point of access, was satisfied by the first VHE prototypes. The challenge in service engineering is now to make these services smarter by adding context management capabilities to them. In this paper w

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5

Moon, Jihun, and Yujin Lim. "A Reinforcement Learning Approach to Access Management in Wireless Cellular Networks." Wireless Communications and Mobile Computing 2017 (2017): 1–7. http://dx.doi.org/10.1155/2017/6474768.

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In smart city applications, huge numbers of devices need to be connected in an autonomous manner. 3rd Generation Partnership Project (3GPP) specifies that Machine Type Communication (MTC) should be used to handle data transmission among a large number of devices. However, the data transmission rates are highly variable, and this brings about a congestion problem. To tackle this problem, the use of Access Class Barring (ACB) is recommended to restrict the number of access attempts allowed in data transmission by utilizing strategic parameters. In this paper, we model the problem of determining

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6

Celentano, Domenico, Antonio Fresa, Maurizio Longo, Fabio Postiglione, and Anton Luca Robustelli. "Secure Mobile IPv6 for Mobile Networks based on the 3GPP IP Multimedia Subsystem." Journal of Communications Software and Systems 3, no. 2 (June 21, 2007): 90. http://dx.doi.org/10.24138/jcomss.v3i2.257.

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The rapid spread of new radio access technologies and the consequent service opportunities have stimulated thetechnical and scientific community to investigate future evolution scenarios for 3rd Generation networks (3G), generically referred to as Beyond-3G or 4G. They are going to be characterized by ever stronger requirements for security, as well as the capability for the final users to experience continuous connectivity and uninterrupted services of IP applications as they move about from one access network to another. Key issues are: i) securityprovision for applications exchanging data i

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7

Prakash, Monika, and Atef Abdrabou. "On the Fidelity of NS-3 Simulations of Wireless Multipath TCP Connections." Sensors 20, no. 24 (December 18, 2020): 7289. http://dx.doi.org/10.3390/s20247289.

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The multipath transmission control protocol (MPTCP) is considered a promising wireless multihoming solution, and the 3rd generation partnership project (3GPP) includes it as a standard feature in the fifth-generation (5G) networks. Currently, ns-3 (Network Simulator-3) is widely used to evaluate the performance of wireless networks and protocols, including the emerging MPTCP protocol. This paper investigates the fidelity of the Linux kernel implementation of MPTCP in the ns-3 direct code execution module. The fidelity of MPTCP simulation is tested by comparing its performance with a real Linux

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8

Lin, Ling, and Antonio Liotta. "Presence in the IP Multimedia Subsystem." Mobile Information Systems 3, no. 3-4 (2007): 187–202. http://dx.doi.org/10.1155/2007/758738.

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With an ever increasing penetration of Internet Protocol (IP) technologies, the wireless industry is evolving the mobile core network towards all-IP network. The IP Multimedia Subsystem (IMS) is a standardised Next Generation Network (NGN) architectural framework defined by the 3rd Generation Partnership Project (3GPP) to bridge the gap between circuit-switched and packet-switched networks and consolidate both sides into on single all-IP network for all services. In this paper, we provide an insight into the limitation of the presence service, one of the fundamental building blocks of the IMS.

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9

Saafi, Salwa, Jiri Hosek, and Aneta Kolackova. "Enabling Next-Generation Public Safety Operations with Mission-Critical Networks and Wearable Applications." Sensors 21, no. 17 (August 28, 2021): 5790. http://dx.doi.org/10.3390/s21175790.

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Public safety agencies have been working on the modernization of their communication networks and the enhancement of their mission-critical capabilities with novel technologies and applications. As part of these efforts, migrating from traditional land mobile radio (LMR) systems toward cellular-enabled, next-generation, mission-critical networks is at the top of these agencies’ agendas. In this paper, we provide an overview of cellular technologies ratified by the 3rd Generation Partnership Project (3GPP) to enable next-generation public safety networks. On top of using wireless communication

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10

Dilli, Ravilla. "Performance analysis of multi user massive MIMO hybrid beamforming systems at millimeter wave frequency bands." Wireless Networks 27, no. 3 (February 4, 2021): 1925–39. http://dx.doi.org/10.1007/s11276-021-02546-w.

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AbstractMillimeter-wave (mmWave) and massive multi-input–multi-output (mMIMO) communications are the most key enabling technologies for next generation wireless networks to have large available spectrum and throughput. mMIMO is a promising technique for increasing the spectral efficiency of wireless networks, by deploying large antenna arrays at the base station (BS) and perform coherent transceiver processing. Implementation of mMIMO systems at mmWave frequencies resolve the issue of high path-loss by providing higher antenna gains. The motivation for this research work is that mmWave and mMI

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11

Zhao, Weijie. "Wen Tong: 5G will be the neural network of the physical world." National Science Review 5, no. 2 (February 20, 2018): 292–96. http://dx.doi.org/10.1093/nsr/nwy025.

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Abstract Smart phones, video, computer games, social platforms and mobile payments have dramatically changed our daily lives in the past 10 years. Behind the rise of the internet industry, fourth-generation (4G) network technology played an instrumental role. According to the plans of major communications companies and the global standardization organization 3GPP (3rd Generation Partnership Project), the next generation of wireless network technology (5G) will start to be commercially used before 2020. What will be the technological improvements in performance of 5G comparing with 4G? Would 5G

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12

Gu, Xinyu, Yiyi Xu, and Jiahan Zhang. "Joint Resource Allocation and Power Control Based on Vehicle’s Motion Characteristics in NOMA-Based V2V Systems." Mobile Information Systems 2020 (November 27, 2020): 1–13. http://dx.doi.org/10.1155/2020/8811067.

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Due to the high spectrum utilization of Nonorthogonal Multiple Access (NOMA), it becomes one of the potential candidate technologies for future wireless communication systems. Meanwhile, in New Radio, Vehicle to Everything (V2X) has been proposed as a promising issue in the 3rd Generation Partnership Project (3GPP). This paper studies the resource allocation mechanism with power control strategy which makes full use of vehicles’ moving characteristics in the NOMA-based Vehicle to Vehicle (V2V) communication system. Firstly, vehicles are grouped according to their moving characteristics by spec

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13

Zhang, Ai Guo, and Qun Yong Wu. "Mobile Cache of CGML Spatial Data." Applied Mechanics and Materials 263-266 (December 2012): 1664–68. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.1664.

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As the development of wireless network and 3rd generation communication, LBS will have broad application prospects. At the same time, CGML spatial data is evolving as the transmission and exchange standard of mobile spatial data because of its compression and rich information. Therefore, a mobile cache strategy of CGML spatial data is proposed. In the strategy, firstly, the basic and expand query boxes are generated in the center of terminal’s location. And then, the cartographic data received in the basic box is formed into CGML file. Finally, the received data in the expand box is added to t

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14

Golovachev, Yosef, Gad A. Pinhasi, and Yosef Pinhasi. "Atmospheric Effects on OFDM Wireless Links Operating in the Millimeter Wave Regime." Electronics 9, no. 10 (September 29, 2020): 1598. http://dx.doi.org/10.3390/electronics9101598.

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The development of millimeter wave communication links and the allocation of bands within the Extremely High Frequency (EHF) range for the next generation cellular network present significant challenges due to the unique propagation effects emerging in this regime of frequencies. This includes susceptibility to amplitude and phase distortions caused by weather conditions. In the current paper, the widely used Orthogonal Division Frequency Multiplexing (OFDM) transmission scheme is tested for resilience against weather-induced attenuation and phase shifts, focusing on the effect of rainfall rat

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15

Kim, Wooseong, and Eun-Kyu Lee. "LTE Network Enhancement for Vehicular Safety Communication." Mobile Information Systems 2017 (2017): 1–18. http://dx.doi.org/10.1155/2017/8923782.

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Direct vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications have been popularly considered for safe driving of manned or unmanned vehicles. The V2I communication is better than the V2V communication for propagating safety messages at critical regions like intersections where the safety messages must be delivered to surround vehicles with low latency and loss, since transmitters as infrastructure can have line of sight to the receiver vehicles and control wireless medium access in a centralized manner unlike V2V. Long-Term Evolution (LTE) cellular networks are rapidly dep

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16

Tahir, Muhammad Naeem, Kari Mäenpää, and Timo Sukuvaara. "Performace Evaluation of Vehicular Communication." Transport and Telecommunication Journal 21, no. 3 (June 1, 2020): 171–80. http://dx.doi.org/10.2478/ttj-2020-0013.

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AbstractModern societies are built on good road infra-structure and efficient transport system. Safety is a high-priority consideration in development of road traffic systems. In recent years the weather information has become becomes very vital for road traffic safety because slippery roads are the key source of road accidents in northern regions of Europe, America and Canada as well. In this article we are presenting the test experiences and pilot road weather related services by executing a set of Vehicle to Infrastructure (V2I) communication scenarios by using IEEE 802.11p and 5G test netw

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17

Ali, Md Sadek, Yu Li, Md Khalid Hossain Jewel, Oluwole John Famoriji, and Fujiang Lin. "Channel Estimation and Peak-to-Average Power Ratio Analysis of Narrowband Internet of Things Uplink Systems." Wireless Communications and Mobile Computing 2018 (July 5, 2018): 1–15. http://dx.doi.org/10.1155/2018/2570165.

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Narrowband Internet of Things (NB-IoT) is a cellular based promising low-power wide-area network (LPWN) technology standardized by the 3rd Generation Partnership Project (3GPP) in release-13 as a part of the future 5th Generation (5G) wireless communication systems. The main design target of NB-IoT was to enhance radio coverage by repeating signal over an additional period of time for the ultralow-end IoT devices that would be operated in extreme coverage environments. But the power efficiency of the low-cost NB-IoT user equipment (NB-IoT UE) in the uplink is the major concern. Coverage improv

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18

Frodigh, M., S. Parkvall, C. Roobol, P. Johansson, and P. Larsson. "Future-generation wireless networks." IEEE Personal Communications 8, no. 5 (October 2001): 10–17. http://dx.doi.org/10.1109/98.960335.

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19

Fry, George E., Albert Jordan, David Y. Lee, Anil S. Sawkar, Nitin J. Shah, and William C. Wiberg. "Next generation wireless networks." Bell Labs Technical Journal 1, no. 2 (August 14, 2002): 88–96. http://dx.doi.org/10.1002/bltj.2017.

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20

Goodman, D. J. "Second generation wireless information networks." IEEE Transactions on Vehicular Technology 40, no. 2 (May 1991): 366–74. http://dx.doi.org/10.1109/25.289417.

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21

Sadiwala, Ritesh C. "Convergence Towards Next Generation Wireless Networks." IOSR Journal of Electrical and Electronics Engineering 4, no. 4 (2013): 1–13. http://dx.doi.org/10.9790/1676-0440113.

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22

Rofougaran, A. R., M. Rofougaran, and A. Behzad. "Radios for next-generation wireless networks." IEEE Microwave Magazine 6, no. 1 (March 2005): 38–43. http://dx.doi.org/10.1109/mmw.2005.1417993.

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23

Lai, Lifeng, Yingbin Liang, and Wenliang Du. "Cooperative Key Generation in Wireless Networks." IEEE Journal on Selected Areas in Communications 30, no. 8 (September 2012): 1578–88. http://dx.doi.org/10.1109/jsac.2012.120924.

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24

Xiang, Yang, Wanlei Zhou, and Haining Wang. "Security in next generation wireless networks." Security and Communication Networks 3, no. 1 (September 25, 2009): 1–3. http://dx.doi.org/10.1002/sec.151.

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25

Hwang, Jenq-Neng. "Wireless MediaNets: application-driven next-generation wireless IP networks." Multimedia Systems 17, no. 4 (November 11, 2010): 251–85. http://dx.doi.org/10.1007/s00530-010-0209-6.

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26

Shimizu, Osamu, Toshiyuki Fujita, Sakahisa Nagai, Hiroshi Fujimoto, and Yoichi Omori. "Development of Dynamic Wireless Power Transfer Coils for 3rd Generation Wireless In-Wheel Motor." IEEJ Transactions on Industry Applications 141, no. 8 (August 1, 2021): 638–45. http://dx.doi.org/10.1541/ieejias.141.638.

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27

Manzoor, Sohaib, Khalid Bashir Bajwa, Muhammad Sajid, Hira Manzoor, Mahak Manzoor, Nouman Ali, and Muhammad Ilyas Menhas. "Modeling of Wireless Traffic Load in Next Generation Wireless Networks." Mathematical Problems in Engineering 2021 (August 30, 2021): 1–15. http://dx.doi.org/10.1155/2021/7293093.

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Software defined WiFi network (SD-WiFi) is a new paradigm that addresses issues such as mobility management, load management, route policies, link discovery, and access selection in traditional WiFi networks. Due to the rapid growth of wireless devices, uneven load distribution among the network resources still remains a challenging issue in SD-WiFi. In this paper, we design a novel four-tier software defined WiFi edge architecture (FT-SDWE) to manage load imbalance through an improved handover mechanism, enhanced authentication technique, and upgraded migration approach. In the first tier, th

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28

Fazal Wahab Karam, and Terje Jensen. "Vertical Handover in Next Generation Wireless Networks." Journal of Next Generation Information Technology 3, no. 4 (November 30, 2012): 10–25. http://dx.doi.org/10.4156/jnit.vol3.issue4.2.

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29

Yarkan, Serhan. "Interference Identification for Next Generation Wireless Networks." Qatar Foundation Annual Research Forum Proceedings, no. 2011 (November 2011): CSO11. http://dx.doi.org/10.5339/qfarf.2011.cso11.

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30

Chandra, Aniruddha, Chayanika Bose, and Manas Kr Bose. "Wireless Relays for Next Generation Broadband Networks." IEEE Potentials 30, no. 2 (March 2011): 39–43. http://dx.doi.org/10.1109/mpot.2011.940778.

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31

Munoz, L., R. Agero, J. Choque, J. A. Lrastorza, L. Sanchez, M. Petrova, and P. Mahonen. "Empowering next-generation wireless personal communication networks." IEEE Communications Magazine 42, no. 5 (May 2004): 64–70. http://dx.doi.org/10.1109/mcom.2004.1299344.

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32

Ekici, Eylem, and Mehmet Can Vuran. "Wireless Heterogeneous Networks and Next Generation Internet." Mobile Networks and Applications 15, no. 5 (March 30, 2010): 607–9. http://dx.doi.org/10.1007/s11036-010-0232-z.

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33

Qian, Yi. "Edge Intelligence for Next Generation Wireless Networks." IEEE Wireless Communications 28, no. 2 (April 2021): 2–3. http://dx.doi.org/10.1109/mwc.2021.9430852.

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34

Albeshri, Ola, Laila Nassef, and Etimad Fadel. "Fuzzy Clustering for Next Generation Wireless Sensor Networks." IJARCCE 8, no. 2 (February 28, 2019): 1–8. http://dx.doi.org/10.17148/ijarcce.2019.8201.

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35

J.Albarakati, Aiman. "An Overview of 4G (4th Generation) Wireless Networks." International Journal of Applied Information Systems 9, no. 2 (June 6, 2015): 21–26. http://dx.doi.org/10.5120/ijais15-451372.

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36

Elkateeb, Ali. "RH-mote for Next-generation Wireless Sensor Networks." Procedia Computer Science 21 (2013): 217–24. http://dx.doi.org/10.1016/j.procs.2013.09.029.

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37

Abdelkader, M., M. Hamdi, and N. Boudriga. "Unifying identity management for fourth generation wireless networks." IET Communications 6, no. 18 (December 18, 2012): 3222–30. http://dx.doi.org/10.1049/iet-com.2011.0303.

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38

Basar, Ertugrul, Miaowen Wen, Raed Mesleh, Marco Di Renzo, Yue Xiao, and Harald Haas. "Index Modulation Techniques for Next-Generation Wireless Networks." IEEE Access 5 (2017): 16693–746. http://dx.doi.org/10.1109/access.2017.2737528.

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Kustiawan, I., T. Hariyadi, and D. R. Nurjannah. "Vertical handoff model in next generation wireless networks." IOP Conference Series: Materials Science and Engineering 850 (May 23, 2020): 012053. http://dx.doi.org/10.1088/1757-899x/850/1/012053.

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40

Chai, Eugene, Kang G. Shin, Jeongkeun Lee, Sung-Ju Lee, and Raul H. Etkin. "Fast Spectrum Shaping for Next-Generation Wireless Networks." IEEE Transactions on Mobile Computing 13, no. 1 (January 2014): 20–34. http://dx.doi.org/10.1109/tmc.2013.125.

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41

Han, Guangjie, Zhangbing Zhou, Longjun Dong, Joel J. P. C. Rodrigues, and Kamesh Namuduri. "Mobility Support for Next-Generation Wireless Sensor Networks." International Journal of Distributed Sensor Networks 12, no. 1 (January 2016): 2462754. http://dx.doi.org/10.1155/2016/2462754.

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Lo Re, Giuseppe, Fabrizio Milazzo, and Marco Ortolani. "Secure random number generation in wireless sensor networks." Concurrency and Computation: Practice and Experience 27, no. 15 (June 6, 2014): 3842–62. http://dx.doi.org/10.1002/cpe.3311.

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Choy, Kwok-Chien, Martin S. Halkyard, Shankar Krishnamoorthy, and Manas R. Panda. "Reusable management frameworks for third-generation wireless networks." Bell Labs Technical Journal 4, no. 4 (August 14, 2002): 171–89. http://dx.doi.org/10.1002/bltj.2197.

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Becchetti, L., S. Leonardi, A. Marchetti-Spaccamela, A. Vitaletti, S. Diggavi, S. Muthukrishnan, and T. Nandagopal. "Parallel scheduling problems in next generation wireless networks." Networks 45, no. 1 (January 2005): 9–22. http://dx.doi.org/10.1002/net.20045.

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Ulema, M., and B. Kozbe. "Management of next-generation wireless networks and services." IEEE Communications Magazine 41, no. 2 (February 2003): 86–87. http://dx.doi.org/10.1109/mcom.2003.1179556.

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Agiwal, Mamta, Abhishek Roy, and Navrati Saxena. "Next Generation 5G Wireless Networks: A Comprehensive Survey." IEEE Communications Surveys & Tutorials 18, no. 3 (2016): 1617–55. http://dx.doi.org/10.1109/comst.2016.2532458.

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Liang, Chengchao, and F. Yu. "Wireless virtualization for next generation mobile cellular networks." IEEE Wireless Communications 22, no. 1 (February 2015): 61–69. http://dx.doi.org/10.1109/mwc.2015.7054720.

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48

Jiang, Chunxiao, Haijun Zhang, Yong Ren, Zhu Han, Kwang-Cheng Chen, and Lajos Hanzo. "Machine Learning Paradigms for Next-Generation Wireless Networks." IEEE Wireless Communications 24, no. 2 (April 2017): 98–105. http://dx.doi.org/10.1109/mwc.2016.1500356wc.

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49

Jiao, Long, Ning Wang, Pu Wang, Amir Alipour-Fanid, Jie Tang, and Kai Zeng. "Physical Layer Key Generation in 5G Wireless Networks." IEEE Wireless Communications 26, no. 5 (October 2019): 48–54. http://dx.doi.org/10.1109/mwc.001.1900061.

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Yu, Heejung, and Yousaf Bin Zikria. "Cognitive Radio Networks for Internet of Things and Wireless Sensor Networks." Sensors 20, no. 18 (September 16, 2020): 5288. http://dx.doi.org/10.3390/s20185288.

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Recent innovation, growth, and deployment of internet of things (IoT) networks are changing the daily life of people. 5G networks are widely deployed around the world, and they are important for continuous growth of IoT. The next generation cellular networks and wireless sensor networks (WSN) make the road to the target of the next generation IoT networks. The challenges of the next generation IoT networks remain in reducing the overall network latency and increasing throughput without sacrificing reliability. One feasible alternative is coexistence of networks operating on different frequenci

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