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Journal articles on the topic 'Cellular network'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Saravanan, K. "A Review on Green Cellular Network." International Journal of Trend in Scientific Research and Development Volume-2, Issue-5 (2018): 342–49. http://dx.doi.org/10.31142/ijtsrd15839.

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Ohipeni, Edwin Angmor Kofi. "5G Cellular Network Forensics." Advances in Multidisciplinary and scientific Research Journal Publication 1, no. 1 (2022): 181–84. http://dx.doi.org/10.22624/aims/crp-bk3-p29.

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The fifth generation (5G) of cellular networks will bring 10Gbps user speeds, have a wider bandwidth which can accommodate 1000 times what the fourth generation (4G) could and 100 times faster than the previous 4G cellular network. This paper’s focus is to highlight on the legal aspects of the 5G cellular network. That is, the health issues, privacy, and security issues on Africans. Most crimes currently are facilitated by cellular network devices and with the improvement that the 5G cellular network brings, there is going to be an increase in cybercrime and hence the need for forensics. These

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3

O. H. Abdelwahed, O. H. Abdelwahed, and M. El-Sayed Wahed. "Optimizing Single Layer Cellular Neural Network Simulator using Simulated Annealing Technique with Neural Networks." Indian Journal of Applied Research 3, no. 6 (2011): 91–94. http://dx.doi.org/10.15373/2249555x/june2013/31.

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4

Fuster, Joaquin M. "Cellular Dynamics of Network Memory." Zeitschrift für Naturforschung C 53, no. 7-8 (1998): 670–76. http://dx.doi.org/10.1515/znc-1998-7-819.

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Abstract One example of “emergence” is the development, as a result of neural ontogeny and living experience, of cortical networks capable of representing and retaining cognitive information. A large body of evidence from neuropsychology, electrophysiology and neuroimaging indicates that so-called working memory and long-term memory share the same neural substrate in the cerebral cortex. That substrate consists in a system of widespread, overlapping and hierarchically organized networks of cortical neurons. In this system, any neuron or group of neurons can be part of many networks, and thus

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5

Zhu, Jia, and Yulong Zou. "Cognitive Network Cooperation for Green Cellular Networks." IEEE Access 4 (2016): 849–57. http://dx.doi.org/10.1109/access.2016.2532600.

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6

Roska, TamÃ¡s, and Giovanni Pazienza. "Cellular neural network." Scholarpedia 4, no. 12 (2009): 1519. http://dx.doi.org/10.4249/scholarpedia.1519.

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7

Kethanan, M., M. Jeyaseelan, and R. Lathersan. "Service Quality and Subscriber Satisfaction of Cellular Network." International Journal of Science and Research (IJSR) 12, no. 12 (2023): 637–40. http://dx.doi.org/10.21275/sr231128101617.

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8

K, Saravanan. "A Review on Green Cellular Network." International Journal of Trend in Scientific Research and Development 2, no. 5 (2018): 342–49. https://doi.org/10.31142/ijtsrd15839.

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Energy efficiency in the cellular network is a growing concern for cellular operators and with the exponential increase in mobile internet traffic driven by a new generation of wireless devices, future cellular networks face a great challenge to meet this overwhelming demand of network capacity. At the same time, the demand for higher data rates and the ever increasing number of wireless users led to rapid increases in power consumption and operating cost of cellular networks. This emerging trend of achieving energy efficiency in cellular networks is motivating the standardization authorities

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9

Tadeusiewicz, Ryszard. "Cellular neural networks (with CNNS [Cellular Neural Network Simulator] software — ver.3.6)." Neurocomputing 8, no. 2 (1995): 224–25. http://dx.doi.org/10.1016/0925-2312(95)90034-9.

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10

Slavova, Angela. "Dynamic properties of cellular neural networks." Journal of Applied Mathematics and Stochastic Analysis 6, no. 2 (1993): 107–16. http://dx.doi.org/10.1155/s1048953393000103.

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Dynamic behavior of a new class of information-processing systems called Cellular Neural Networks is investigated. In this paper we introduce a small parameter in the state equation of a cellular neural network and we seek for periodic phenomena. New approach is used for proving stability of a cellular neural network by constructing Lyapunov's majorizing equations. This algorithm is helpful for finding a map from initial continuous state space of a cellular neural network into discrete output. A comparison between cellular neural networks and cellular automata is made.

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11

SHIN, Won-Yong, and Bang Chul JUNG. "Network Coordinated Opportunistic Beamforming in Downlink Cellular Networks." IEICE Transactions on Communications E95-B, no. 4 (2012): 1393–96. http://dx.doi.org/10.1587/transcom.e95.b.1393.

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12

Elsawy, Hesham, Hayssam Dahrouj, Tareq Y. Al-naffouri, and Mohamed-slim Alouini. "Virtualized cognitive network architecture for 5G cellular networks." IEEE Communications Magazine 53, no. 7 (2015): 78–85. http://dx.doi.org/10.1109/mcom.2015.7158269.

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13

Nussinov, Ruth, Chung-Jung Tsai, and Peter Csermely. "Allo-network drugs: harnessing allostery in cellular networks." Trends in Pharmacological Sciences 32, no. 12 (2011): 686–93. http://dx.doi.org/10.1016/j.tips.2011.08.004.

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14

Azari, Amin, and Guowang Miao. "Network Lifetime Maximization for Cellular-Based M2M Networks." IEEE Access 5 (2017): 18927–40. http://dx.doi.org/10.1109/access.2017.2753283.

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15

HAENGGI, MARTIN. "DISTRIBUTED SENSOR NETWORKS: A CELLULAR NONLINEAR NETWORK PERSPECTIVE." International Journal of Neural Systems 13, no. 06 (2003): 405–14. http://dx.doi.org/10.1142/s0129065703001686.

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Large-scale networks of integrated wireless sensors become increasingly tractable. Advances in hardware technology and engineering design have led to dramatic reductions in size, power consumption, and cost for digital circuitry, and wireless communications. Networking, self-organization, and distributed operation are crucial ingredients to harness the sensing, computing, and computational capabilities of the nodes into a complete system. This article shows that those networks can be considered as cellular nonlinear networks (CNNs), and that their analysis and design may greatly benefit from t

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Kanehisa, Minoru, Miho Furumichi, Yoko Sato, Mari Ishiguro-Watanabe, and Mao Tanabe. "KEGG: integrating viruses and cellular organisms." Nucleic Acids Research 49, no. D1 (2020): D545—D551. http://dx.doi.org/10.1093/nar/gkaa970.

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Abstract KEGG (https://www.kegg.jp/) is a manually curated resource integrating eighteen databases categorized into systems, genomic, chemical and health information. It also provides KEGG mapping tools, which enable understanding of cellular and organism-level functions from genome sequences and other molecular datasets. KEGG mapping is a predictive method of reconstructing molecular network systems from molecular building blocks based on the concept of functional orthologs. Since the introduction of the KEGG NETWORK database, various diseases have been associated with network variants, which

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17

Gamst, A., E. G. Zinn, R. Beck, and R. Simon. "Cellular Radio Network Planning." IEEE Aerospace and Electronic Systems Magazine 1, no. 2 (1986): 8–11. http://dx.doi.org/10.1109/maes.1986.5005038.

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18

Khadim, Saima, Adnan Waqar, Aamir Zeb, Imran Khan, and Izhar Hussain. "Smart Cognitive Cellular Network." International Journal of Future Generation Communication and Networking 10, no. 12 (2017): 23–34. http://dx.doi.org/10.14257/ijfgcn.2017.10.12.03.

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19

SHIMODAIRA, Hidekazu, Gia Khanh TRAN, Kei SAKAGUCHI, Kiyomichi ARAKI, Shinobu NANBA, and Satoshi KONISHI. "Diamond Cellular Network —Optimal Combination of Small Power Basestations and CoMP Cellular Networks —." IEICE Transactions on Communications E99.B, no. 4 (2016): 917–27. http://dx.doi.org/10.1587/transcom.2015ebp3224.

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20

Yue Ma, Yue Ma, Xin Li Yue Ma, and Jianbin Li Xin Li. "A Security Edge Computing Offloading Solution for 5G Cellular Network." 電腦學刊 32, no. 6 (2021): 015–23. http://dx.doi.org/10.53106/199115992021123206002.

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21

Chen-Wei Feng, Chen-Wei Feng, Xian-Guo Lu Chen-Wei Feng, Yu Sun Xian-Guo Lu, Huang-Bin Zeng Yu Sun, and Zhuo Li Huang-Bin Zeng. "Vehicle Clustering and Resource Allocation Algorithm Based on Cellular Network." 電腦學刊 34, no. 3 (2023): 031–47. http://dx.doi.org/10.53106/199115992023063403003.

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<p>As a special Mobile Ad-hoc Network (MANET), Vehicular Ad-hoc Network (VANET) plays a very important role in the future intelligent transportation system. In order to solve the problems of unstable communication connection, fast network topology change and low communication resource utilization caused by high vehicle mobility in VANET, a low-complexity resource allocation algorithm based on vehicle cluster is proposed. Firstly, considering the speed, position and moving direction of the vehicles, a vehicle clustering algorithm based on movement consistency is proposed to cluster the ve

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22

Zhang, Xiaoxia, Zhongming Zheng, Qinghua Shen, Jing Liu, Xuemin Sherman Shen, and Liang-Liang Xie. "Optimizing Network Sustainability and Efficiency in Green Cellular Networks." IEEE Transactions on Wireless Communications 13, no. 2 (2014): 1129–39. http://dx.doi.org/10.1109/twc.2013.122713.131133.

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23

Shnaiwer, Yousef N., Sameh Sorour, Parastoo Sadeghi, Neda Aboutorab, and Tareq Y. Al-Naffouri. "Network-Coded Macrocell Offloading in Femtocaching-Assisted Cellular Networks." IEEE Transactions on Vehicular Technology 67, no. 3 (2018): 2644–59. http://dx.doi.org/10.1109/tvt.2017.2771416.

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24

Torrea-Duran, Rodolfo, Maximo Morales Cespedes, Jorge Plata-Chaves, Luc Vandendorpe, and Marc Moonen. "Topology-Aware Space-Time Network Coding in Cellular Networks." IEEE Access 6 (2018): 7565–78. http://dx.doi.org/10.1109/access.2017.2773709.

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25

Menachi, Eliav, and Ran Giladi. "Hierarchical Ethernet Transport Network Architecture for backhaul cellular networks." Wireless Networks 19, no. 8 (2013): 1933–43. http://dx.doi.org/10.1007/s11276-013-0578-9.

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26

Hiremath, Madhu N. "Software Defined Network (SDN) and OpenFlow Protocol in 5G Network." International Journal for Research in Applied Science and Engineering Technology 12, no. 11 (2024): 2028–36. http://dx.doi.org/10.22214/ijraset.2024.65548.

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The world is moving at a high speed in the implementation and innovations of new systems and gadgets. 3G and 4G networks support currently wireless network communications. However, the networks are deemed to be slow and fail to receive signals or data transmission to various regions because of solving the problem. This paper will analyze the use of Software Defined Network (SDN) in a 5G (fifth generation) network that can be faster and reliable. Further, in Mobile IP, there exist triangulation problems between the sending and receiving nodes along with latency issues during handoff for the mob

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27

Hasan Al-Bowarab, Mustafa, Nurul Azma Zakaria, Zaheera Zainal Abidin, and Ziadoon Kamil Maseer. "Review on Device-to-Device Communication in Cellular based Network Systems." International Journal of Engineering & Technology 7, no. 3.20 (2018): 435. http://dx.doi.org/10.14419/ijet.v7i3.20.20587.

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In a traditional cellular-network based system, the devices are not allowed to be interconnected directly in the certified mobile bandwidth, and all communications are carried out via the base station (BS). At present, device terminal broadcasting allows devices in the distributed network to act as transmitting relays to each other and reach a massive ad hoc network of networks that is different from the previous cellular architecture that faces technical challenges. Therefore, this article explores the application of a cellular-based two-layer network system that includes a base station (BS)

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28

Cheng, Peng, Andrew R. Weily Weily, and Y. Jay Guo. "Towards 5th Generation Cellular Mobile Networks." Journal of Telecommunications and the Digital Economy 2, no. 2 (2014): 14. https://doi.org/10.18080/jtde.v2n2.328.

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Cellular mobile networks have enabled ubiquitous communications and largely changed the way we live and work. At the same time, the network itself has been undergoing significant changes in the process of meeting our ever increasing demands on data rate and quality of service. In this article, we show the path of the evolution in both standards and techniques and provide our vision for the future of the cellular networks. We review the evolution of international standards for cellular mobile networks in the last two decades, describe how the network layout has been migrating from rigid cellula

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29

Yunita Yunita, Muhammad Aziz Nur Mubarok, Arjuna Fikri Tri Firmansyah, and Didik Aribowo. "Penggunaan Software Cisco Packet Tracer Dalam Simulasi Jaringan Seluler Pada Pembelajaran Materi Terminal Telkomunikasi." Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika 2, no. 3 (2024): 26–33. http://dx.doi.org/10.61132/jupiter.v2i3.270.

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Cellular networks play an important role in modern life with the availability of flexible connectivity in various places, fast internet access and communication services and are a reference for innovation and economic growth. However, the complexity of cellular networks requires careful planning and management, this is to ensure a reliable and safe service. The method used in designing cellular networks is the simulation method, namely by using Cisco Packet Tracer software and literature studies from various references. The results of cellular network simulations using this software can show s

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30

Rajule, Nilakshee, Mithra Venkatesan, Radhika Menon, and Anju Kulkarni. "Network Traffic Prediction with Reduced Power Consumption towards Green Cellular Networks." International Journal of Computer Network and Information Security 15, no. 6 (2023): 64–77. http://dx.doi.org/10.5815/ijcnis.2023.06.06.

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The increased number of cellular network subscribers is giving rise to the network densification in next generation networks further increasing the greenhouse gas emission and the operational cost of network. Such issues have ignited a keen interest in the deployment of energy-efficient communication technologies rather than modifying the infrastructure of cellular networks. In cellular network largest portion of the power is consumed at the Base stations (BSs). Hence application of energy saving techniques at the BS will help reduce the power consumption of the cellular network further enhanc

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31

Lam, Patrick, and Soung Liew. "Nested Network Mobility on the Multihop Cellular Network." IEEE Communications Magazine 45, no. 9 (2007): 100–104. http://dx.doi.org/10.1109/mcom.2007.4342863.

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32

Chandramohan, B. "Restructured Ant Colony Optimization Routing Protocol for Next Generation Network." International Journal of Computers Communications & Control 10, no. 4 (2015): 492. http://dx.doi.org/10.15837/ijccc.2015.4.665.

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Wireless network is a major research domain in the past few decades. Wireless network evolves in many forms like cellular communication, ad hoc network, vehicular network, mesh network and sensor network. Next generation network is a recent cellular communication which provides heterogeneous connectivity on cellular communication. The routing in next generation wireless networks is an important research issue which requires many constraints than wired networks. Hence, Ant Colony Optimization (ACO) is applied in this paper for routing in heterogeneous next generation wireless network. The ACO i

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33

Zhang, Dehai, Linan Liu, Cheng Xie, Bing Yang, and Qing Liu. "Citywide Cellular Traffic Prediction Based on a Hybrid Spatiotemporal Network." Algorithms 13, no. 1 (2020): 20. http://dx.doi.org/10.3390/a13010020.

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With the arrival of 5G networks, cellular networks are moving in the direction of diversified, broadband, integrated, and intelligent networks. At the same time, the popularity of various smart terminals has led to an explosive growth in cellular traffic. Accurate network traffic prediction has become an important part of cellular network intelligence. In this context, this paper proposes a deep learning method for space-time modeling and prediction of cellular network communication traffic. First, we analyze the temporal and spatial characteristics of cellular network traffic from Telecom Ita

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Saad, Iqbal, Khan Alamgir, Wasim Khan Hassan, Khan Imran, and Muhammad Fazal. "Performance Enhancement of Heterogeneous Cellular Networks Using Vertical Handover." International Journal of Engineering Works (ISSN: 2409-2770) 06, no. 02 (2019): 44–49. https://doi.org/10.5281/zenodo.2565880.

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  In seamless and fast mobility, smooth handover is one of the major challenges in small cell heterogeneous cellular networks. This paper focuses on the phenomenon of vertical handover for wireless heterogeneous networks. This class of networks can be grounded on the parameter values such as bandwidth availability, received signal strength, call request/served per unit time (mean), power dissipation, consumption of power, duration of mobile station presence, network security, cost of the network and velocity of the mobile station. The proposed system, in this paper, is characterized on th

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35

Lorincz, Josip. "Energy-Efficient Wireless Cellular Communications through Network Resource Dynamic Adaptation." International Journal of Business Data Communications and Networking 9, no. 2 (2013): 11–26. http://dx.doi.org/10.4018/jbdcn.2013040102.

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Cellular networks represent one of the major energy consumers of communication networks and their contribution to the global carbon footprint and energy consumption continuously and rapidly increases. Improving energy efficiency of the cellular access networks become an important requirement and has recently gained considerable attention of the research community and operators. In this paper, improving cellular networks energy efficiency through dynamic adaptation of network resources is presented with foundations which justify practical realization of such approach. Paper gives insight into h

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36

MawjoudA, Dr S. Abdul, and T. Hussien. "Capacity Enhancement InWCDMA Cellular Network." AL-Rafdain Engineering Journal (AREJ) 20, no. 1 (2012): 110–22. http://dx.doi.org/10.33899/rengj.2012.47164.

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37

Pandey, Aunkita, Arindam Satpati, and Somnath Sardar. "BRAND LOYALTY FOR CELLULAR NETWORK." International Journal of Management, Public Policy and Research 1, no. 1 (2022): 68–75. http://dx.doi.org/10.55829/ijmpr.v1i1.44.

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The Indian telecom industry is a very dynamic industry with very stiff competition amongst existing service providers in the telecom markets. But the brand loyalty among the customers gets difficult because of this competition. So, it gets necessary what consumers want and what can satisfy them. In that context the present papers are the research of 201 consumers as well as respondents of finding the attributes and factors for making the consumers loyal and stay connected to one brand only. The research was done by Google form in Gujarat state with the relevant literature review of the researc

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38

Gaur, Rajneesh K. "Cellular Network Based Drug Monitoring." Asia Pacific Journal of Public Health 23, no. 6 (2011): 1025–26. http://dx.doi.org/10.1177/1010539511422741.

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Pharmacovigilance is a resourceful process for monitoring adverse drug reactions. The lack of resources in developing countries makes it difficult to execute pharamcovigilance programs on a large scale. Therefore, the cellular technology based network, which has widespread access in the developing world, may be used as an inexpensive means of monitoring.

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39

Saha, D., and S. E. Kay. "Cellular digital packet data network." IEEE Transactions on Vehicular Technology 46, no. 3 (1997): 697–706. http://dx.doi.org/10.1109/25.618195.

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40

Jamal, A. M. M. "Neural Network and Cellular Manufacturing." Industrial Management & Data Systems 93, no. 3 (1993): 21–25. http://dx.doi.org/10.1108/02635579310027343.

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41

Kung, Jaeha, Duckhwan Kim, and Saibal Mukhopadhyay. "Adaptive Precision Cellular Nonlinear Network." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 26, no. 5 (2018): 841–54. http://dx.doi.org/10.1109/tvlsi.2018.2794498.

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42

Kuusik, Alar, Takeo Hisada, Satoshi Suzuki, and Katsuhisa Furuta. "Cellular Network Telecontrolled Robot Vehicle." IFAC Proceedings Volumes 37, no. 7 (2004): 99–104. http://dx.doi.org/10.1016/s1474-6670(17)32131-6.

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43

de-la-Bandera, Isabel, David Palacios, Jessica Mendoza, and Raquel Barco. "Feature Extraction for Dimensionality Reduction in Cellular Networks Performance Analysis." Sensors 20, no. 23 (2020): 6944. http://dx.doi.org/10.3390/s20236944.

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Next-generation mobile communications networks will have to cope with an extraordinary amount and variety of network performance indicators, causing an increase in the storage needs of the network databases and the degradation of the management functions due to the high-dimensionality of every network observation. In this paper, different techniques for feature extraction are described and proposed as a means for reducing this high dimensionality, to be integrated as an intermediate stage between the monitoring of the network performance indicators and their usage in mobile networks’ managemen

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M. Dhasaratham, Et al. "Big Data Network Optimization for Mobile Cellular Networks in 5G." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 10 (2023): 1924–30. http://dx.doi.org/10.17762/ijritcc.v11i10.8783.

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5G ensures the provision of intelligent network and application services by means of connectivity to remote sensors, massive amounts of Internet of Things data, and fast data transmissions. Through the utilization of distributed compute architectures and by supporting massive connectivity across diverse devices like sensors, gateways, and controllers, 5G brings about a transformative revolution in the conversion of both big data at rest and data in motion into real-time intelligence. Big Data Analytics play an important role in the evolution of 5G standards, enabling intelligence across networ

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Liang, Bin, Mark A. Gregory, and Shuo Li. "Latency Analysis for Mobile Cellular Network uRLLC Services." Journal of Telecommunications and the Digital Economy 10, no. 3 (2022): 39–57. http://dx.doi.org/10.18080/jtde.v10n3.447.

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The fifth generation (5G) mobile network technologies include ultra-Reliable Low Latency Communications (uRLLC) capability. To fully exploit uRLLC, distributed Multi- access Edge Computing (MEC) is being developed and introduced at the network edge with an architecture that supports applications and services. Some of the MEC applications will benefit from uRLLC, including virtual reality, augmented reality, education, health, online gaming, automatic manufacturing and Vehicle-to-everything. However, unique challenges and opportunities exist for 5G cellular networks and MEC due to a range of fa

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46

Singh, Avinash, Surya Pratap Singh, Arvind Kumar Maurya, and Upendra Nath Tripathi. "Combined Strategy for Cellular Traffic Congestion Management." International Journal of Emerging Research in Management and Technology 6, no. 8 (2018): 12. http://dx.doi.org/10.23956/ijermt.v6i8.113.

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In wireless media, congestion is usual phenomenon that arises due abruptly raised subscribers demand to establish connections congruently in particular cell at mean real time. Generally, the congestion problem occurs in cellular network traffic and almost persists in every generation. Every mobile network operators is facing this problem every day and struggling to resolve this issue but not being success yet. As more advance cellular devices are being in demand and its users are also being increasing which turns to demand larger bandwidth requirements from cellular subscriber. Presently for c

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47

Kahali, Sayan, Marcus E. Raichle, and Dmitriy A. Yablonskiy. "The Role of the Human Brain Neuron–Glia–Synapse Composition in Forming Resting-State Functional Connectivity Networks." Brain Sciences 11, no. 12 (2021): 1565. http://dx.doi.org/10.3390/brainsci11121565.

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While significant progress has been achieved in studying resting-state functional networks in a healthy human brain and in a wide range of clinical conditions, many questions related to their relationship to the brain’s cellular constituents remain. Here, we use quantitative Gradient-Recalled Echo (qGRE) MRI for mapping the human brain cellular composition and BOLD (blood–oxygen level-dependent) MRI to explore how the brain cellular constituents relate to resting-state functional networks. Results show that the BOLD signal-defined synchrony of connections between cellular circuits in network-d

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48

Huang, Chien-Hung, Efendi Zaenudin, Jeffrey J. P. Tsai, Nilubon Kurubanjerdjit, Eskezeia Y. Dessie, and Ka-Lok Ng. "Dissecting molecular network structures using a network subgraph approach." PeerJ 8 (August 6, 2020): e9556. http://dx.doi.org/10.7717/peerj.9556.

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Biological processes are based on molecular networks, which exhibit biological functions through interactions of genetic elements or proteins. This study presents a graph-based method to characterize molecular networks by decomposing the networks into directed multigraphs: network subgraphs. Spectral graph theory, reciprocity and complexity measures were used to quantify the network subgraphs. Graph energy, reciprocity and cyclomatic complexity can optimally specify network subgraphs with some degree of degeneracy. Seventy-one molecular networks were analyzed from three network types: cancer n

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Shoewu, O.O. "Performance Evaluation Of Mobile Cellular Networks In Nigeria." J. of Advancement in Engineering and Technology 6, no. 3 (2018): 05. https://doi.org/10.5281/zenodo.1250262.

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The aim of this paper is to evaluate the performance of mobile networks such as MTN, GLO, and ETISALAT in Nigeria and suggest ways the performance of digital cellular networks can improve to minimize some of its present short comings or limitations. This paper discusses the performance improvement of digital cellular networks. A non- CDMA cellular network is use in an overall wireless environment for the purpose of this paper. This paper also discusses the performance assessment of three mobile network operators. In addition, ways to minimize the limitations in other to improve the performance

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Qiushi, Sun, He Yang, and Ovanes Petrosian. "Graph Attention Network Enhanced Power Allocation for Wireless Cellular System." Informatics and Automation 23, no. 1 (2024): 259–83. http://dx.doi.org/10.15622/ia.23.1.9.

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The importance of an efficient network resource allocation strategy has grown significantly with the rapid advancement of cellular network technology and the widespread use of mobile devices. Efficient resource allocation is crucial for enhancing user services and optimizing network performance. The primary objective is to optimize the power distribution method to maximize the total aggregate rate for all customers within the network. In recent years, graph-based deep learning approaches have shown great promise in addressing the challenge of network resource allocation. Graph neural networks

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