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Journal articles on the topic 'Multi-RAT'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Monteiro, Victor Farias, Marten Ericson, and Francisco Rodrigo P. Cavalcanti. "Fast-RAT Scheduling in a 5G Multi-RAT Scenario." IEEE Communications Magazine 55, no. 6 (2017): 79–85. http://dx.doi.org/10.1109/mcom.2017.1601094.

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2

Gadde, Nagaraja, Basavaraj Jakkali, Ramesh Babu Halasinanagenahalli Siddamallaih, and Gowrishankar Gowrishankar. "Quality of experience aware network selection model for service provisioning in heterogeneous network." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 2 (2022): 1839. http://dx.doi.org/10.11591/ijece.v12i2.pp1839-1848.

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Heterogeneous wireless networks (HWNs) are capable of integrating the different radio access technologies that make it possible to connect mobile users based on the performance parameters. Further quality of service (QoS) is one of the major topics for HWNs, moreover existing radio access technology (RAT) methodology are designed to provide network QoS criteria. However, limited work has been carried out for the RAT selection mechanism considering user QoS preference and existing models are developed based on the multi-mode terminal under a given minimal density network. For overcoming researc

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3

Nagaraja, Gadde, Jakkali Basavaraj, Babu Halasinanagenahalli Siddamallaih Ramesh, and Gowrishankar. "Quality of experience aware network selection model for service provisioning in heterogeneous network." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 2 (2022): 1839–48. https://doi.org/10.11591/ijece.v12i2.pp1839-1848.

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Heterogeneous wireless networks (HWNs) are capable of integrating the different radio access technologies that make it possible to connect mobile users based on the performance parameters. Further quality of service (QoS) is one of the major topics for HWNs, moreover existing radio access technology (RAT) methodology are designed to provide network QoS criteria. However, limited work has been carried out for the RAT selection mechanism considering user QoS preference and existing models are developed based on the multi-mode terminal under a given minimal density network. For overcoming researc

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4

Kim, Cheolhoon, SeungGwan Lee, and Sungwon Lee. "Multi-Device to Multi-Device (MD2MD) Content-Centric Networking Based on Multi-RAT Device." Symmetry 9, no. 12 (2017): 291. http://dx.doi.org/10.3390/sym9120291.

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5

Zakrzewska, Anna, David Lopez-Perez, Lester Ho, Holger Claussen, and Haris Gacanin. "Cell ID Management in Multi-Vendor and Multi-RAT Heterogeneous Networks." IEEE Transactions on Network and Service Management 16, no. 2 (2019): 417–29. http://dx.doi.org/10.1109/tnsm.2019.2903494.

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6

Diez, Luis, Andres Garcia-Saavedra, Victor Valls, Xi Li, Xavier Costa-Perez, and Ramon Aguero. "LaSR: A Supple Multi-Connectivity Scheduler for Multi-RAT OFDMA Systems." IEEE Transactions on Mobile Computing 19, no. 3 (2020): 624–39. http://dx.doi.org/10.1109/tmc.2018.2876847.

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7

Sepulcre, Miguel, and Javier Gozalvez. "Heterogeneous V2V Communications in Multi-Link and Multi-RAT Vehicular Networks." IEEE Transactions on Mobile Computing 20, no. 1 (2021): 162–73. http://dx.doi.org/10.1109/tmc.2019.2939803.

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8

Yu, Guanding, Yuhuan Jiang, Lukai Xu, and Geoffrey Ye Li. "Multi-Objective Energy-Efficient Resource Allocation for Multi-RAT Heterogeneous Networks." IEEE Journal on Selected Areas in Communications 33, no. 10 (2015): 2118–27. http://dx.doi.org/10.1109/jsac.2015.2435374.

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9

Marvi, Murk, Adnan Aijaz, and Muhammad Khurram. "Toward a Unified Framework for Analysis of Multi-RAT Heterogeneous Wireless Networks." Wireless Communications and Mobile Computing 2019 (January 3, 2019): 1–19. http://dx.doi.org/10.1155/2019/6918637.

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The increased penetration of different radio access technologies (RATs) and the growing trend towards their convergence necessitates the investigation of wireless heterogeneous networks (HetNets) from coverage and capacity perspective. This paper develops a unified framework for signal-to-interference-plus-noise ratio and rate coverage analysis of multi-RAT HetNets, with each RAT employing either a contention-free or a contention-based channel access strategy. The proposed framework adopts tools from stochastic geometry, with the location of APs and mobile users modeled through independent Poi

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10

Shi, Qing, Hiroyuki Ishii, Katsuaki Tanaka, et al. "Behavior modulation of rats to a robotic rat in multi-rat interaction." Bioinspiration & Biomimetics 10, no. 5 (2015): 056011. http://dx.doi.org/10.1088/1748-3190/10/5/056011.

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11

MORAITOU, Marina, Meropi PATRINOU-GEORGOULA, and Apostolia GUIALIS. "Structural/functional properties of a mammalian multi-component structure containing all major spliceosomal small nuclear ribonucleoprotein particles." Biochemical Journal 332, no. 1 (1998): 135–44. http://dx.doi.org/10.1042/bj3320135.

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An approx. 40 S multi-component structure, consisting of all major spliceosomal small nuclear ribonucleoprotein particles (snRNP) (U1, U2, U4/U6 and U5) in stable association with a large number of polypeptides, mainly in the range 50–210 kDa, has been reported to exist within rat liver nuclear extracts [Guialis, Moraitou, Patrinou-Georgoula and Dangli (1991) Nucleic Acids Res. 19, 287–296]. Using a new polyclonal antibody recognizing a 63 kDa protein component of the complex, this multi-snRNP assembly was detected within rat liver nuclear extracts as efficiently as with the antibody for the U

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12

Więcek, Dariusz, Igor Michalski, Krzysztof Rzeźniczak, and Dariusz Wypiór. "Multi-RAT Orchestration Method for Heterogeneous Wireless Networks." Applied Sciences 11, no. 18 (2021): 8281. http://dx.doi.org/10.3390/app11188281.

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Currently, energy efficiency (EE) of wireless communication is essential where many wireless networks with different Radio Access Technologies (RATs) coexist together. The RATs can be effectively selected and managed on a higher level to achieve maximum EE and save energy, e.g., save batteries. The approach to wireless traffic steering in mobile networks with a proof-of-concept solution is presented in this paper, owing to the developed high-level multi-RAT (multi-Radio Access Technology) heterogonous network orchestration approach. Based on the high-level network orchestrator, which traces ne

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13

Wu, Huici, Xiaofeng Tao, Na Li, and Jin Xu. "Secrecy Outage Probability in Multi-RAT Heterogeneous Networks." IEEE Communications Letters 20, no. 1 (2016): 53–56. http://dx.doi.org/10.1109/lcomm.2015.2499748.

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14

Monteiro, Victor Farias, Diego Aguiar Sousa, Tarcisio Ferreira Maciel, Francisco Rodrigo Porto Cavalcanti, Carlos F. M. e. Silva, and Emanuel Bezerra Rodrigues. "Distributed RRM for 5G Multi-RAT Multiconnectivity Networks." IEEE Systems Journal 13, no. 1 (2019): 192–203. http://dx.doi.org/10.1109/jsyst.2018.2838335.

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15

Daradjat Natawigena, Wahyu, Ichsan Nurul Bari, and Md Sirajul Islam Khan. "Innovative Multi-Aroma Rodenticides for Effective Rat Management." Outlooks on Pest Management 36, no. 1 (2025): 3–9. https://doi.org/10.1564/v36_feb_02.

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Different rat species exhibit varying preferences for the smell and taste of poisonous bait, which are influenced by their specific species and habitat. There are three common rodent species in agricultural and urban areas including Rattus argentiventer, Rattus norvegicus and Mus musculus. Understanding these preferences is essential for developing effective rodenticides that cater to multiple species. This study aims to find quality rodenticides that the wider community needs and meet consumer demands. These rodenticides can control various species of rat pests in agriculture and settlements

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16

Hatsukade, Yoshimi, K. Noda, S. Masaki, S. Yoshida, and Saburo Tanaka. "Multi-Channel High-T_c SQUID System for Bio-Applications." Solid State Phenomena 152-153 (April 2009): 424–27. http://dx.doi.org/10.4028/www.scientific.net/ssp.152-153.424.

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high-Tc SQUID, magnetometer, bio-magnetism, multi-channel, rat MCG. Abstract. Three-channel directly-coupled-type high-Tc SQUID magnetometer array, with pick-up coil size of 1.5 mm2 comparable to the lift-off distance of the developed multi-channel SQUID system, was designed. In this design, two slits were introduced in the SQUID ring to improve the inductive coupling between the pick-up coil and the SQUID ring to obtain the field sensitivity of about 700 fT/Hz1/2. With the SQUID array that was mounted on the multi-channel SQUID system, the measurements of magnetocardiogram of rat were demonst

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17

Farhat, Anwar, H. Masud Mosharrof, ul Islam Khan Burhan, F. Olanrewaju Rashidah, and A. Latif Suhaimi. "Radio Access Technology (RAT) Selection Mechanism using TOPSIS Method in Heterogeneous Wireless Networks (HWN)." Indonesian Journal of Electrical Engineering and Computer Science 12, no. 2 (2018): 852–64. https://doi.org/10.11591/ijeecs.v12.i2.pp852-864.

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In next-generation wireless networks, a Multi-Mode Device (MMD) can be connected with available Radio Access Technology (RAT) in a Heterogeneous Wireless Network (HWN). The appropriate RAT selection is essential to achieve expected Quality of Service (QoS) in HWN. There are many factors to select an appropriate RAT in HWN including Data rate, Power consumption, Security, Network delay, Service price, etc. Nowadays, the MMDs are capable to handle with multiple types of services like voice, file downloading, video streaming. Considering numerous factors and multiple types of services, it is a gr

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18

Anwar, Farhat, Mosharrof Masud, Burhan Ul Islam, and Rashidah Funke Olanrewaju. "Radio Access Technology (RAT) Selection Mechanism using TOPSIS Method in Heterogeneous Wireless Networks (HWN)." Indonesian Journal of Electrical Engineering and Computer Science 12, no. 2 (2018): 852. http://dx.doi.org/10.11591/ijeecs.v12.i2.pp852-864.

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<p>In next-generation wireless networks, a Multi-Mode Device (MMD) can be connected with available Radio Access Technology (RAT) in a Heterogeneous Wireless Network (HWN). The appropriate RAT selection is essential to achieve expected Quality of Service (QoS) in HWN. There are many factors to select an appropriate RAT in HWN including Data rate, Power consumption, Security, Network delay, Service price, etc. Nowadays, the MMDs are capable to handle with multiple types of services like voice, file downloading, video streaming. Considering numerous factors and multiple types of services, i

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19

Klapez, Martin, Carlo Augusto Grazia, and Maurizio Casoni. "The Energy Footprint of 5G Multi-RAT Cellular Architectures." IEEE Access 9 (2021): 144493–504. http://dx.doi.org/10.1109/access.2021.3122797.

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20

Kim, Jihwan, Hyang-Won Lee, and Song Chong. "Super-MAC Design for Tightly Coupled Multi-RAT Networks." IEEE Transactions on Communications 67, no. 10 (2019): 6939–51. http://dx.doi.org/10.1109/tcomm.2019.2930515.

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21

Basaras, Pavlos, George Iosifidis, Stepan Kucera, and Holger Claussen. "Multicast Optimization for Video Delivery in Multi-RAT Networks." IEEE Transactions on Communications 68, no. 8 (2020): 4973–85. http://dx.doi.org/10.1109/tcomm.2020.2993878.

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22

Yan, Mu, Gang Feng, Jianhong Zhou, and Shuang Qin. "Smart Multi-RAT Access Based on Multiagent Reinforcement Learning." IEEE Transactions on Vehicular Technology 67, no. 5 (2018): 4539–51. http://dx.doi.org/10.1109/tvt.2018.2793186.

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23

Törős, István, and Péter Fazekas. "Energy efficient radio network planning including multi-RAT perspective." International Journal of Mobile Network Design and Innovation 6, no. 3 (2016): 121. http://dx.doi.org/10.1504/ijmndi.2016.078977.

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24

Yamamoto, K., E. Kobayashi, A. Ogami, and Y. Morimoto. "Multi-Walled Carbon Nanotubes Intratracheally Instilled in Rat Lung." Microscopy and Microanalysis 16, S2 (2010): 1262–63. http://dx.doi.org/10.1017/s1431927610053742.

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25

Burmeister, David M., Tamer AbouShwareb, Karl-Erik Andersson, and George J. Christ. "MULTI-DISCIPLINARY STUDIES OF DE NOVO RAT BLADDER REGENERATION." Journal of Urology 181, no. 4S (2009): 77–78. http://dx.doi.org/10.1016/s0022-5347(09)60223-8.

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26

Schwerdt, Helen N., Min Jung Kim, Satoko Amemori, et al. "Subcellular probes for neurochemical recording from multiple brain sites." Lab on a Chip 17, no. 6 (2017): 1104–15. http://dx.doi.org/10.1039/c6lc01398h.

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27

Manor, Tami, Efrat Barbiro-Michaely, Genady Rogatsky, and Avraham Mayevsky. "Real-time multi-site multi-parametric monitoring of rat brain subjected to traumatic brain injury." Neurological Research 30, no. 10 (2008): 1075–83. http://dx.doi.org/10.1179/174313208x346107.

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28

Zhang, Guanglin, Qingying Meng, Montgomery Blencowe, Rahul Agrawal, Fernando Gomez‐Pinilla, and Xia Yang. "Multi‐Tissue Multi‐Omics Nutrigenomics Indicates Context‐Specific Effects of Docosahexaenoic Acid on Rat Brain." Molecular Nutrition & Food Research 64, no. 23 (2020): 2000788. http://dx.doi.org/10.1002/mnfr.202000788.

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29

Irshad, Tayyaba, Rafi-us Shan, Raja Wasim Ahmad, Abbas Khalid, and Siti Hafizah Ab Hamid. "MULTI-RAT BASED ADAPTIVE QUALITY OF SERVICE (QOS) MANAGEMENT IN WBAN." Malaysian Journal of Computer Science 33, no. 4 (2020): 252–69. http://dx.doi.org/10.22452/mjcs.vol33no4.1.

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Wireless body area network (WBAN), a sub-branch of wireless sensor networks (WSN), helps continuous monitoring of various conditions and states of a human body. It has vast application areas, including self-care, battlefield, health, sports, assisted living, and entertainment. In WBAN, sensors (e.g., ECG, EEG, EMG, and temperature) may transmit sensed information of the subject under observation to a personal server which directs it to the main server for the analysis. The requirement of an application in terms of reliability and delay varies depending on the situation and environment. For ins

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30

Ядав, М., та П. К. Сингхал. "Метод назначения перемежителя для поддержки технологий множественного радиодоступа в сетях 5G". Известия высших учебных заведений. Радиоэлектроника 64, № 2 (2021): 117–24. http://dx.doi.org/10.20535/s0021347021020059.

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Сети связи пятого поколения (5G) поддерживают несколько технологий радиодоступа, широко известные как multi-RAT, для облегчения обслуживания всех абонентов мобильной связи, независимо от того, абонентами какой сети старого поколения они являются. Назначение уникального перемежителя каждому активному мобильному абоненту в рамках связи внутри RAT является сравнительно простой задачей. Однако это становится сложной проблемой, когда приходится иметь дело с поддержкой связи с несколькими RAT. В данной статье представлено теоретическое решение передачи специальных сигналов управления, позволяющее пр

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31

Mourice Otieno Ojijo, Dismas Ombuya, Andrew Kipkebut, Wyclife Ayako, and Cleophas Mochoge. "A Reinforcement Learning Approach to Service Based User Admission in a Multi-Tier 5G Wireless Networks." Kabarak Journal of Research & Innovation 11, no. 3 (2021): 240–50. http://dx.doi.org/10.58216/kjri.v11i3.69.

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The expected massive connectivity in 5G wireless network is bound to become a challenge to service providers. Many services over the 5G network will be aligned to a particular radio access network (RAN). As a result admitting a service based user to a particular RAN will depend on the most efficient radio access technology selection (RAT). This is because 5G network will adopt multi-tier radio access networks ranging from high power macro base stations to extremely low power Bluetooth connectivity. Selection of a service oriented RAT is critical because some wireless services have superior qua

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32

Debnath, Sanjoy, Anand Jee, Debarati Sen, Srimanta Baishya, and Wasim Arif. "Energy Efficient Optimal Resource Allocation in Multi-RAT Heterogeneous Network." Applied Artificial Intelligence 35, no. 15 (2021): 2246–75. http://dx.doi.org/10.1080/08839514.2021.1998300.

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33

Thomas, Rohan. "Acute Oral Rat Toxicity Study of Multi-herbal formulation (ECD0058)." International Journal of Pure & Applied Bioscience 4, no. 3 (2016): 73–79. http://dx.doi.org/10.18782/2320-7051.2317.

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34

Eng Hwee Ong and Jamil Y. Khan. "On optimal network selection in a dynamic multi-RAT environment." IEEE Communications Letters 14, no. 3 (2010): 217–19. http://dx.doi.org/10.1109/lcomm.2010.03.092378.

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35

Ohyama, Yoshihiko, Osamu Masumoto, Emiko Usui, and Kyuichiro Okuda. "Multi-Functional Property of Rat Liver Mitochondrial Cytochrome P-4501." Journal of Biochemistry 109, no. 3 (1991): 389–93. http://dx.doi.org/10.1093/oxfordjournals.jbchem.a123391.

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36

Lin, Kate Ching-Ju, Hao-Chen Wang, Yuan-Cheng Lai, and Ying-Dar Lin. "Communication and Computation Offloading for Multi-RAT Mobile Edge Computing." IEEE Wireless Communications 26, no. 6 (2019): 180–86. http://dx.doi.org/10.1109/mwc.001.1800603.

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37

Litaudon, Philippe, and Martine Cattarelli. "Multi-site optical recording of the rat piriform cortex activity." NeuroReport 5, no. 7 (1994): 743–46. http://dx.doi.org/10.1097/00001756-199403000-00001.

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38

Driscoll, I., S. R. Howard, J. C. Stone, et al. "The aging hippocampus: A multi-level analysis in the rat." Neuroscience 139, no. 4 (2006): 1173–85. http://dx.doi.org/10.1016/j.neuroscience.2006.01.040.

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39

Yang, Shun-Neng, Shu-Wei Ho, Yi-Bing Lin, and Chai-Hien Gan. "A multi-RAT bandwidth aggregation mechanism with software-defined networking." Journal of Network and Computer Applications 61 (February 2016): 189–98. http://dx.doi.org/10.1016/j.jnca.2015.11.003.

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40

Mansouri, Wahida, Kais Mnif, Faouzi Zarai, Mohammad S. Obaidat, and Lotfi Kamoun. "A new multi-rat scheduling algorithm for heterogeneous wireless networks." Journal of Systems and Software 115 (May 2016): 174–84. http://dx.doi.org/10.1016/j.jss.2015.02.073.

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41

Galanopoulos, Apostolos, Fotis Foukalas, and Theodoros A. Tsiftsis. "Multi-RAT Aggregation Through Spectrum Reallocation for Future Wireless Networks." Wireless Personal Communications 111, no. 3 (2019): 1545–62. http://dx.doi.org/10.1007/s11277-019-06939-1.

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42

Steidl, Esther-Marie, Estelle Neveu, Daniel Bertrand, and Bruno Buisson. "The adult rat hippocampal slice revisited with multi-electrode arrays." Brain Research 1096, no. 1 (2006): 70–84. http://dx.doi.org/10.1016/j.brainres.2006.04.034.

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43

Das, Dibakar, and Debabrata Das. "Efficient UE mobility in multi-RAT cellular networks using SDN." Wireless Networks 25, no. 1 (2017): 255–67. http://dx.doi.org/10.1007/s11276-017-1555-5.

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44

Chen, Gang, Shibo Cui, Lin You, Yan Li, Yun-Hui Mei, and Xu Chen. "Experimental study on multi-step creep properties of rat skins." Journal of the Mechanical Behavior of Biomedical Materials 46 (June 2015): 49–58. http://dx.doi.org/10.1016/j.jmbbm.2015.02.020.

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45

Rakovic, Valentin, Aleksandar Ichkov, Simona Marinova, Davor Todorovski, Vladimir Atanasovski, and Liljana Gavrilovska. "Dynamic Virtual Resource Allocation in Virtualized multi-RAT Cellular Networks." Wireless Personal Communications 97, no. 2 (2017): 1677–92. http://dx.doi.org/10.1007/s11277-017-4568-6.

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46

Gavrilovska, Liljana, Valentin Rakovic, and Aleksandar Ichkov. "Virtualization Approach for Machine-Type Communications in Multi-RAT Environment." Wireless Personal Communications 100, no. 1 (2018): 67–79. http://dx.doi.org/10.1007/s11277-018-5611-y.

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47

Verbanck, S., E. R. Weibel, and M. Paiva. "Simulations of washout experiments in postmortem rat lungs." Journal of Applied Physiology 75, no. 1 (1993): 441–51. http://dx.doi.org/10.1152/jappl.1993.75.1.441.

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We developed a rat lung model to simulate single-breath and multiple-breath washout experiments performed by Verbanck et al. (J. Appl. Physiol. 71: 847–854, 1991) and Gonzalez Mangado et al. (J. Appl. Physiol. 71: 855–862, 1991). The multi-branch-point rat lung model is based on anatomic data of the rat airway tree as obtained by Rodriguez et al. (Am. J. Anat. 180: 143–155, 1987). We simulated single- and multiple-breath washout maneuvers and computed the slope of the alveolar plateaus and Fowler and Bohr dead spaces. In general, the comparison between experiments and simulations shows a good

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48

Nathalie Mitton and Brandon Foubert. "RODENT: a flexible TOPSIS based routing protocol for multi-technology devices in wireless sensor networks." ITU Journal on Future and Evolving Technologies 2, no. 1 (2021): 89–100. http://dx.doi.org/10.52953/fkro8431.

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Wireless Sensor Networks (WSN) are efficient tools for many use cases, such as environmental monitoring. However WSN deployment is sometimes limited by the characteristics of the Radio Access Technologies (RATs) they use. To overcome some of these limitations, we propose to leverage the use of a Multiple Technologies Network (MTN). What we refer to as MTN is a network composed of nodes which are able to use several RAT and communicating wirelessly through multi-hop paths. The management of the RAT and routes must be handled by the nodes themselves, in a local and distributed way, with a

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49

Escudero-Garzás, J. J., and C. Bousoño-Calzón. "An Analysis of the Network Selection Problem for Heterogeneous Environments with User-Operator Joint Satisfaction and Multi-RAT Transmission." Wireless Communications and Mobile Computing 2017 (2017): 1–13. http://dx.doi.org/10.1155/2017/7425412.

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The trend in wireless networks is that several wireless radio access technologies (RATs) coexist in the same area, forming heterogeneous networks in which the users may connect to any of the available RATs. The problem of associating a user to the most suitable RAT, known as network selection problem (NSP), is of capital importance for the satisfaction of the users in these emerging environments. However, also the satisfaction of the operator is important in this scenario. In this work, we propose that a connection may be served by more than one RAT by using multi-RAT terminals. We formulate t

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50

Kang, Haw Yuan, Raja Rina Raja Ikram, Kamal Zuhairi Zamli, and Nurul Akmar Binti Emran. "Exploring Multifactorial Techniques in Rat Swarm Optimization: Preliminary Results." Engineering, Technology & Applied Science Research 15, no. 3 (2025): 23430–35. https://doi.org/10.48084/etasr.10690.

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Test Suite Reduction (TSR) is a critical optimization challenge in software testing that aims to reduce the number of test cases while maintaining maximum requirement coverage. Traditional algorithms, such as the Rat Swarm Optimizer (RSO), struggle with scalability, especially when dealing with large datasets. Additionally, RSO is unable to solve multiple tasks simultaneously, which leads to an increased time to complete the optimization process across multiple datasets. To resolve this constraint, this paper introduces the Multi-Factorial Rat Swarm Optimizer (MFRSO), which combines Multi-Fact

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