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Relevant bibliographies by topics / Radio Resources Allocation

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Academic literature on the topic 'Radio Resources Allocation'

Author: Grafiati

Published: 25 January 2025

Last updated: 31 July 2025

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Journal articles on the topic "Radio Resources Allocation"

1

Ma, Lu, Xiangming Wen, Luhan Wang, Zhaoming Lu, Raymond Knopp, and Irfan Ghauri. "A Biological Model for Resource Allocation and User Dynamics in Virtualized HetNet." Wireless Communications and Mobile Computing 2018 (September 27, 2018): 1–11. http://dx.doi.org/10.1155/2018/1745904.

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Virtualization technology is considered an effective measure to enhance resource utilization and interference management via radio resource abstraction in heterogeneous networks (HetNet). The critical challenge in wireless virtualization is virtual resource allocation on which substantial works have been done. However, most existing researches on virtual resource allocation focus on improving total utility. Different from the existing works, we investigate the dynamic-aware virtual radio resource allocation in virtualization based HetNet considering utility and fairness. A virtual radio resour

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Maule, Massimiliano, John Vardakas, and Christos Verikoukis. "Multi-service network slicing 5G NR orchestration via tailored HARQ scheme design and hierarchical resource scheduling." Multi-Service Network Slicing 5G NR Orchestration via Tailored HARQ Scheme Design and Hierarchical Resource Scheduling 72, no. 4 (2022): 5021–34. https://doi.org/10.1109/TVT.2022.3223252.

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In the radio access network domain, novel applications' requirements and network dynamics claim scalable processing capabilities, decentralized architecture, and on-demand resource allocation. Due to the intrinsic heterogeneous nature of the network resources, a fully context-aware fronthaul management is extremely complex to design. Operators have a high level-of-abstraction of the infrastructure's resources, which limits their decision-making capabilities. In this paper, a novel radio access network orchestrator is proposed, which jointly combines network function placement and resource allo

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.., Ishwarlal, and Ankit Saxena. "Design, Simulation and Analysis of Multi-Dimensional Multiple Access (MDMA) Schemes Using MATLAB for Quality of Service (QoS) Enhancement." Journal of Intelligent Systems and Internet of Things 11, no. 2 (2024): 111–28. http://dx.doi.org/10.54216/jisiot.110210.

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To provide better Quality of Service (QoS), which is expected in contemporary 6G wireless networks. We project a MDMA scheme to fulfill UE-specific QoS needs with the aid of multi-dimensional radio resource cost. This method can be successfully called Multi-Dimensional Radio Resource Allocation (MDRA). Specifically, the planned scheme incorporates two novel aspects: for each UE, the choice of user-specific non-orthogonal multiple approach mode whose cost is determined by UE-specific non-orthogonal interference cancellation; and allocating multiple dimensional radio resources for co-existing UE

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Benmammar, Badr. "Recent Advances on Artificial Intelligence in Cognitive Radio Networks." International Journal of Wireless Networks and Broadband Technologies 9, no. 1 (2020): 27–42. http://dx.doi.org/10.4018/ijwnbt.2020010102.

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Cognitive radio is a form of wireless communication that makes decisions about allocating and managing radio resources after detecting its environment and analyzing the parameters of its radio frequency environment. Decision making in cognitive radio can be based on optimization techniques. In this context, machine learning and artificial intelligence are to be used in cognitive radio networks in order to reduce complexity, obtain resource allocation in a reasonable time and improve the user's quality of service. This article presents recent advances on artificial intelligence in cognitive rad

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R G, Umesh, Sushil Kumar G N, Santhosh K, Suraksha M S, and Dr Praveen Kumar K V. "Radio Resource Allocation for 5G Network Using Deep Reinforcement Learning." International Journal for Research in Applied Science and Engineering Technology 11, no. 3 (2023): 677–83. http://dx.doi.org/10.22214/ijraset.2023.49468.

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Abstract: Resource allocation is a critical task in 5Gnetworks that determines how network resources are assigned to different devices and services. Traditional methods rely on predefined rules or heuristics, which may not always be optimal. Deep reinforcement learning (DRL)is a promising approach for radio resource allocation in 5Gnetworks as it can learn to optimize resource allocation based on feedback from the network. In DRL, an agent learns to make decisions based on rewards and penalties received from the environment. In radio resource allocation, the agent would learn to allocate resou

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Mathew, Alex. "SliceOptiAI: Smart Resource Allocation for Seamless Network Slicing." International Journal of Computer Science and Mobile Computing 13, no. 1 (2024): 82–87. http://dx.doi.org/10.47760/ijcsmc.2024.v13i01.006.

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An AI-driven model for resource allocation in network slicing is examined in this research paper. The model’s algorithm comprises three stages, each with its specific algorithm. Resource allocation begins with reservation, where the controller reserves minimum resources for each slice. The second stage is autonomous radio resource management, mainly focusing on AI model training and decision engines. The last stage is physical resource allocation, where resources are distributed to the slices and users. Simulations on MATLAB software indicated this model to be effective in enhancing resource a

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Wulandari, Astri, Nachwan Mufti Adriansyah, and Vinsensius Sigit Widhi Prabowo. "Greedy Based Radio Resource Allocation Algorithm with SARSA Power Control Scheme in D2D Underlaying Communication." Journal of Measurements, Electronics, Communications, and Systems 7, no. 1 (2020): 6. http://dx.doi.org/10.25124/jmecs.v7i1.3472.

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Device-to-Device (D2D) underlaying communication system is a solution in reducing the workload of eNodeB and increasing the system data rate. This communication system consists of two users, namely Cellular User Equipment (CUE) and D2D pair, where CUE will share its resources with the D2D pair. This sharing resources also causes interference and should be managed using the resource allocation algorithm. In this work, the resource allocation scheme occurs in a single cell with an uplink communication direction. The resource allocation process uses greedy and joint greedy algorithms. After CUE a

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Yadav, Savita, Pradeep Kumar Shah, Sowmiya Kumar, and Anjali Singh. "Enhancing resource allocation for power sharing in cognitive radio communication networks using ensemble moth-flame optimized dynamic recurrent neural networks." Multidisciplinary Science Journal 6 (July 12, 2024): 2024ss0307. http://dx.doi.org/10.31893/multiscience.2024ss0307.

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Wireless data transmission networks are radio communication networks (RCN). These networks allow radios as well as phones to communicate, exchange data and calls across radio waves. Broadcasting, emergency services and mobile telecommunications are among the numerous industries that use RCN's flexibility and ease. Our proposed method, Ensemble Moth-Flame Optimized Dynamic Recurrent Neural Network (EMFO-DRNN), addresses the challenges inherent in DNN-based systems, maximizing power distribution, minimizing interference and optimizing spectrum utilization. This solution enables adaptive channel

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Mathonsi, Topside E., Tshimangadzo Mavin Tshilongamulenzhe, and Bongisizwe Erasmus Buthelezi. "Enhanced Resource Allocation Algorithm for Heterogeneous Wireless Networks." Journal of Advanced Computational Intelligence and Intelligent Informatics 24, no. 6 (2020): 763–73. http://dx.doi.org/10.20965/jaciii.2020.p0763.

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In heterogeneous wireless networks, service providers typically employ multiple radio access technologies to satisfy the requirements of quality of service (QoS) and improve the system performance. However, many challenges remain when using modern cellular mobile communications radio access technologies (e.g., wireless local area network, long-term evolution, and fifth generation), such as inefficient allocation and management of wireless network resources in heterogeneous wireless networks (HWNs). This problem is caused by the sharing of available resources by several users, random distributi

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Razmi, Shirin, and Naser Parhizgar. "Adaptive resources assignment in OFDM-based cognitive radio systems." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 3 (2019): 1935. http://dx.doi.org/10.11591/ijece.v9i3.pp1935-1943.

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Spectrum efficiency of orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems can be improved by adaptive resources allocation. In resources allocation, transmission resources such as modulation level and transmission power are adaptively assigned based on channel variations. The goal of this paper is maximize the total transmission rate of secondary user (SU). Hence, we investigate adaptive power and modulation allocation to achieve this purpose. For power allocation, we investigate optimal and conventional methods and then introduce a novel suboptimal algorithm

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Dissertations / Theses on the topic "Radio Resources Allocation"

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Weng, Lingfan. "Analysis and allocation of radio resources in cooperative wireless networks /." View abstract or full-text, 2008. http://library.ust.hk/cgi/db/thesis.pl?ECED%202008%20WENG.

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Sharara, Mahdi. "Resource Allocation in Future Radio Access Networks." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG024.

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Cette thèse considère l'allocation des ressources radio et de calcul dans les futurs réseaux d'accès radio et plus précisément dans les réseaux Cloud-RAN (Cloud-Radio Access Networks) ainsi que les réseaux Open-RAN (Open-Radio Access Networks). Dans ces architectures, le traitement en bande de base de plusieurs stations de base est centralisé et virtualisé. Cela permet une meilleure optimisation du réseau et une réduction des dépenses d'investissement et d'exploitation. Dans la première partie de cette thèse, nous considérons un schéma de coordination entre les ordonnanceurs radio et de calcul

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Schimuneck, Matias Artur Klafke. "Adaptive Monte Carlo algorithm to global radio resources optimization in H-CRAN." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2017. http://hdl.handle.net/10183/169922.

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Até 2020 espera-se que as redes celulares aumentam em dez vezes a área de cobertura, suporte cem vezes mais equipamentos de usuários e eleve a capacidade da taxa de dados em mil vezes, comparada as redes celulares atuais. A densa implantação de pequenas células é considerada uma solução promissora para alcançar essas melhorias, uma vez que aproximar as antenas dos usuários proporciona maiores taxas de dados, devido à qualidade do sinal em curtas distâncias. No entanto, operar um grande número de antenas pode aumentar significativamente o consumo de energia da infraestrutura de rede. Além disso

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Amer, Asmaa. "Resource Allocation in NOMA-based cellular networks." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASG089.

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Cette thèse vise à optimiser l'allocation des ressources au sein des systèmes NOMA, en particulier les systèmes NOMA coopératifs en liaison descendante, dans des configurations de stations de base à antenne unique et à antennes multiples. L'objectif est de maximiser l'efficacité spectrale et énergétique, tout en proposant des schémas NOMA plus efficaces qui peuvent tirer parti des avantages du NOMA et répondre aux limitations des schémas actuellement considérés en termes de consommation d'énergie et de complexité des récepteurs. Dans la première contribution, un système NOMA coopératif basé su

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Masmoudi, Raouia. "Télécommunications domotiques efficaces en termes de consommation d’énergie." Thesis, Cergy-Pontoise, 2015. http://www.theses.fr/2015CERG0791.

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Le spectre électromagnétique est une ressource limitée dont l'usage doit être optimisé. Plusieurs travaux actuels visent à améliorer l'utilisation des fréquences radio en exploitant les méthodes de traitement intelligent du signal : la radio cognitive. Cette thèse se place dans ce contexte. Concrètement, nous considérons un problème d'allocation conjointe de spectre et de puissance dans un système radio cognitif (CR) composé de plusieurs utilisateurs secondaires (SUs) et primaires (PUs). L'objectif est d'optimiser l'efficacité énergétique des SUs tout en garantissant des niveaux d'interférence

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Suliman, I. M. (Isameldin Mohammed). "Performance analysis of cognitive radio networks and radio resource allocation." Doctoral thesis, Oulun yliopisto, 2016. http://urn.fi/urn:isbn:9789526212753.

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Abstract Cognitive radio (CR) is becoming a promising tool for solving the problem of the scarce radio resource and spectrum inefficiency. Spectrum sensing (signal detection) enables real-time detection of spectrum holes by unlicensed secondary users (SUs) in cognitive radio networks (CRNs). In this thesis, performance analysis of CRNs and radio resource allocation are considered. A continuous time Markov chain (CTMC) based analytical model taking into account all relevant elements as well as addressing the issue of the false alarm rate (FAR) associated with the continuous sensing is developed

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Ellingsæter, Brage Høyland. "Cognitive Radio: Interference Management and Resource Allocation." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for elektronikk og telekommunikasjon, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-11295.

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In this thesis the performance of different cognitive systems are analyzed in different environments and scenarios. The main scenarios are: one cognitive and one primary user, multiple cognitive users and channels and multiple cognitive and primary users. With primary users in the vicinity, cognitive systems are evaluated both when no degradation to primary user QoS is allowed and when some degradation is allowed, measured by an outage probability. In all scenarios involving one or more primary users, the performance is evaluated over two phases. In Phase 1 the channel is idle, i.e. the primar

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Hashmi, Ziaul Hasan. "Dynamic resource allocation for cognitive radio systems." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/961.

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Cognitive Radio (CR) is considered to be a novel approach to improve the underutilization of precious radio resources by exploiting the unused licensed spectrum in dynamically changing environments. Designing efficient resource allocation algorithms for dynamic spectrum sharing and for power allocation in OFDM-CR networks is still a challenging problem. In this thesis, we specifically deal with these two problems. Dynamic spectrum sharing for the unlicensed secondary users (SU)s with device coordination could minimize the wastage of the spectrum. But this is a feasible approach only if the n

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Wong, Chung Kit. "Resource allocation for multihop packet radio networks." Thesis, McGill University, 1994. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=68059.

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This thesis focuses on the routing, power control and channel allocation of Packet Radio Network (PRnet) with multiple channels. The Nearest Forward with Progress (NFP) routing policy is known to achieve higher throughput in the single channel setting than the Most Forward with Progress (MFP) strategy. This observation motivates our work on the variant of the Shacham/King model in which MFR is replaced by NFP in a multi-channel case. The resulting network shows that the superiority of NFP relative to MFP persists. Another way to improve network performance is to control the network topology by

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Ngo, Duy. "Radio resource allocation for wireless heterogeneous networks." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=119622.

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By deploying small cells (i.e., femtocells) within the same service area of regular macrocells, a much higher area spectral efficiency, better indoor coverage, and significant mobile data offloading can be achieved at low cost. Because femtocells reuse the radio spectrum already assigned to macrocells in an uncoordinated fashion, new cell boundaries are created and the signal interference situation becomes far more unpredictable than in conventional networks. In this heterogeneous network setting, adaptive power allocation and dynamic spectrum access are needed to ensure a harmonized coexisten

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Books on the topic "Radio Resources Allocation"

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Jean-Marc, Chaduc, and Pogorel Gerard, eds. The radio spectrum: Managing a strategic resource. Wiley, 2008.

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Benmammar, Badr, and Asma Amraoui. Radio Resource Allocation and Dynamic Spectrum Access. John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118575116.

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Karl, Nebbia, and United States. National Telecommunications and Information Administration, eds. Spectrum resource assessment of unlicensed electronic devices. U.S. Dept. of Commerce, National Telecommunications and Information Administration, 1985.

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Yŏnʼguwŏn, Hanʼguk Chŏnja Tʻongsin, ред. Chŏnpʻa chawŏn iyong kiban kisul kaebal =: Development of basic spectrum resource utilizing technology. Chŏngbo Tʻongsinbu, 2007.

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Yŏnʼguwŏn, Hanʼguk Chŏnja Tʻongsin, ред. Chŏnpʻa chawŏn iyong kiban kisul kaebal =: Development of basic spectrum resource utilizing technology. Chŏngbo Tʻongsinbu, 2007.

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Le-Ngoc, Tho, and Khoa Tran Phan. Radio Resource Allocation Over Fading Channels Under Statistical Delay Constraints. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57693-0.

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Fernando, Xavier, Ajmery Sultana, Sattar Hussain, and Lian Zhao. Cooperative Spectrum Sensing and Resource Allocation Strategies in Cognitive Radio Networks. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-73957-1.

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1971-, Chen Huan, ed. Radio resource management for multimedia QoS support in wireless networks. Kluwer Academic Publishers, 2004.

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Carvalho, Nuno Borges, Alessandro Cidronali, and Roberto Gómez-García. White space communication technologies. Cambridge University Press, 2015.

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Underwood, Caroline D. Spectrum issues for the new communications age. Edited by Griswold Mary E and Moore, L. K. S. (Linda K. S.). Nova Science Publishers, 2010.

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Book chapters on the topic "Radio Resources Allocation"

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Vivier, Emmanuelle, Michel Terré, and Bernard Fino. "On the Complexity of Radio Resources Allocation in WCDMA Systems." In IFIP International Federation for Information Processing. Springer US, 2005. http://dx.doi.org/10.1007/0-387-23150-1_16.

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Houda, Mzoughi, Faouzi Zarai, Mohammad S. Obaidat, Balqies Sadoun, and Lotfi Kamoun. "Cooperative Radio Resources Allocation and Congestion Prevention Scheme for LTE-A." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69832-8_17.

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Mikaeil, Ahmed Mohammed, and Weisheng Hu. "Q-Learning Based Joint Allocation of Fronthaul and Radio Resources in Multiwavelength-Enabled C-RAN." In Optical Network Design and Modeling. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38085-4_53.

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Wang, Shaowei. "Dynamic Resource Allocation." In Cognitive Radio Networks. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08936-2_2.

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Ghorbanzadeh, Michael, and Ahmed Abdelhadi. "Radio Resource Block Allocation." In Practical Channel-Aware Resource Allocation. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73632-3_4.

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Ghorbanzadeh, Mo, Ahmed Abdelhadi, and Charles Clancy. "Radio Resource Block Allocation." In Cellular Communications Systems in Congested Environments. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46267-7_6.

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Benmammar, Badr, and Asma Amraoui. "Cognitive Radio." In Radio Resource Allocation and Dynamic Spectrum Access. John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118575116.ch2.

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Ghorbanzadeh, Michael, and Ahmed Abdelhadi. "Utility Functions and Radio Resource Allocation." In Practical Channel-Aware Resource Allocation. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73632-3_2.

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Kazmi, S. M. Ahsan, Latif U. Khan, Nguyen H. Tran, and Choong Seon Hong. "Network Slicing: Radio Resource Allocation." In Network Slicing for 5G and Beyond Networks. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16170-5_4.

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Zhang, Huaqing, and Zhu Han. "Distributed Resource Allocation for Network Virtualization." In Handbook of Cognitive Radio. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-1389-8_39-1.

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Conference papers on the topic "Radio Resources Allocation"

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Purushotham, Pidugu, S. Ramacharan, I. Ravi Prakash Reddy, and A. Vijaya Krishna. "Allocation of Green Spectrum Resources in Cognitive Radio Networks." In 2024 Intelligent Systems and Machine Learning Conference (ISML). IEEE, 2024. https://doi.org/10.1109/isml60050.2024.11007447.

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Upadhyay, Deepak, Mridul Gupta, Kunj Bihari Sharma, Abhay Upadhyay, and Satya Prakash Yadav. "Optimization of New Radio Physical Uplink Shared Channel Resources Allocation with Efficient Demodulated Referenced Signals and PT-RE Deployment." In 2024 International Conference on Electrical Electronics and Computing Technologies (ICEECT). IEEE, 2024. http://dx.doi.org/10.1109/iceect61758.2024.10738873.

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Vijayasarveswari, V., S. Khatun, M. M. Fakir, M. N. Nayeem, L. M. Kamarudin, and A. Jakaria. "Cognitive radio based optimal channel sensing and resources allocation." In 11TH ASIAN CONFERENCE ON CHEMICAL SENSORS: (ACCS2015). Author(s), 2017. http://dx.doi.org/10.1063/1.4975292.

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de Souza, Phelipe A., Abdallah S. Abdallah, Elivelton F. Bueno, and Kleber V. Cardoso. "Virtualized Radio Access Networks: Centralization, Allocation, and Positioning of Resources." In 2018 IEEE International Conference on Communications Workshops (ICC Workshops). IEEE, 2018. http://dx.doi.org/10.1109/iccw.2018.8403667.

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Vijayasarveswari, V., S. Khatun, and M. N. Morshed. "Performance of spectrum sensing in cognitive radio for resources allocation." In PROCEEDINGS OF GREEN DESIGN AND MANUFACTURE 2020. AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0044715.

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Wang, Chiapin, Yu-Chia Liu, Han-Chi Gao, and Tsung-Yi Fan Chiang. "Reinforcement-Learning Based Radio Resources Allocation in Licensed Assisted Access." In 2020 IEEE International Conference on Smart Cloud (SmartCloud). IEEE, 2020. http://dx.doi.org/10.1109/smartcloud49737.2020.00040.

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Jun, Wang, and Zhu Jinzhou. "Q-learning Based Radio Resources Allocation in Cognitive Satellite Communication." In 2022 International Symposium on Networks, Computers and Communications (ISNCC). IEEE, 2022. http://dx.doi.org/10.1109/isncc55209.2022.9851730.

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Malde, Keval A., Venkatarami Reddy Chintapalli, Bhavishya Sharma, Bheemarjuna Reddy Tamma, and A. Antony Franklin. "JARS: A Joint Allocation of Radio and System Resources for Virtualized Radio Access Networks." In NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium. IEEE, 2023. http://dx.doi.org/10.1109/noms56928.2023.10154407.

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Boskov, Ivan, and Ales Svigelj. "Dynamic allocation of resources in a heterogeneous Cloud Radio Access Network." In 2022 International Conference on Broadband Communications for Next Generation Networks and Multimedia Applications (CoBCom). IEEE, 2022. http://dx.doi.org/10.1109/cobcom55489.2022.9880676.

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Mzoughi, Houda, Faouzi Zarai, and Lotfi Kamoun. "Interference-limited radio resources allocation in LTE_A system with MIH cooperation." In 2016 22nd Asia-Pacific Conference on Communications (APCC). IEEE, 2016. http://dx.doi.org/10.1109/apcc.2016.7581465.

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Reports on the topic "Radio Resources Allocation"

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Lamarque, Hugh, and Hannah Brown. Key considerations: Mpox in the Busia-Malaba border region linking Uganda and Kenya. Institute of Development Studies, 2025. https://doi.org/10.19088/sshap.2025.022.

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Mpox has spread along the Busia-Malaba border that links eastern Uganda and western Kenya, with risk factors centred on cross-border mobility. Community responses to mpox are shaped by access to information on radio, television and social media as well as local terminologies, understandings of disease aetiology, spiritual and religious beliefs, household structures and cross-border mobility patterns. Despite vaccine allocations from the World Health Organization (WHO), the response has been hindered by resource constraints, mistrust and cross-border challenges. This brief summarises findings o

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Bruce. L52090 Near-Neutral pH SCC - Dormancy and Re-Initiation of Stress Corrosion Cracks. Pipeline Research Council International, Inc. (PRCI), 2003. http://dx.doi.org/10.55274/r0011360.

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The objective of this research project was to identify the environmental, metallurgical, and mechanical conditions that lead to dormancy and re-initiation of previously dormant stress corrosion cracks. These parameters would assist pipeline operators in mitigating near-neutral pH SCC on their systems, and allocating resources for pipeline maintenance. Unload-reload transients were found to increase the crack growth rate in the majority of the experiments and to re-initiate dormant stress corrosion cracks in several cases. On the other hand, there was no consistent effect of the presence or mag

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Albert, Jose Ramon, Ronald Mendoza, Deanne Lorraine Cabalfin, Mohammad Mahmoud, and Mika Muñoz. A Process Evaluation of the Philippine Alternative Learning System. Philippine Institute for Development Studies, 2024. https://doi.org/10.62986/dp2024.31.

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This study presents a comprehensive process evaluation of the Department of Education's Alternative Learning System (ALS) in the Philippines, examining its effectiveness in providing second-chance education opportunities for out-of-school youth and adults (OSYAs). While the ALS plays a vital role in the Philippine education system, systematic evidence on its implementation effectiveness, operational processes, and institutional capabilities has been limited thus far. The study employs a mixed-methods approach, combining quantitative analysis of administrative data with key informant interviews

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Almaden, Catherine Roween. Economics of Satellite Campuses. Philippine Institute for Development Studies, 2024. https://doi.org/10.62986/dp2024.33.

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This research provides a comprehensive comparison of the financial, educational, and socio-spatial considerations in establishing State Universities and Colleges (SUCs) satellite campuses versus enhancing support mechanisms for existing SUCs in the Philippines. It highlights their critical role in expanding access to higher education, particularly for underserved and geographically isolated communities. Building on literature that identifies satellite campuses as tools for addressing educational disparities and fostering regional socio-economic development, the study emphasizes cost-effectiven

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Financial Stability Report - First Half of 2023. Banco de la República, 2024. http://dx.doi.org/10.32468/rept-estab-fin.sem1.eng-2023.

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Abstract:

Banco de la República’s main goal is to preserve the purchasing power of the currency in coordination with the general economic policy that is intended to stabilize output and employment at long-term sustainable levels. Properly meeting the goal assigned to the Bank by the 1991 Constitution critically depends on preserving financial stability. This is understood to be a general condition in which the financial system channels domestic savings and evaluates and manages the financial risks in a way that facilitates the performance of the economy and efficient allocation of resources while, at th

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6

Financial Stability Report - First Half of 2022. Banco de la República, 2023. http://dx.doi.org/10.32468/rept-estab-fin.sem1.eng-2022.

Full text

Abstract:

Banco de la República’s main objective is to preserve the purchasing power of the currency in coordination with the general economic policy that is intended to stabilize output and employment at long-term sustainable levels. Properly meeting the goal assigned to the Bank by the 1991 Constitution critically depends on preserving financial stability. This is understood to be a general condition in which the financial system evaluates and manages the financial risks in a way that facilitates the economy’s performance and efficient allocation of resources while, at the same time, it is able to, on

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7

Financial Stability Report - Second Half of 2022. Banco de la República, 2023. http://dx.doi.org/10.32468/rept-estab-fin.sem2.eng-2022.

Full text

Abstract:

Banco de la República’s main goal is to preserve the purchasing power of the currency in coordination with the general economic policy that is intended to stabilize output and employment at long-term sustainable levels. Properly meeting the goal assigned to the Bank by the 1991 Constitution critically depends on preserving financial stability. This is understood to be a general condition in which the financial system evaluates and manages the financial risks in a way that facilitates the suitable performance of the economy and efficient allocation of resources while, at the same time, it is ab

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