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Journal articles on the topic 'Radio Resources Allocation'

Author: Grafiati

Published: 25 January 2025

Last updated: 19 July 2025

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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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Shirin, Razmi, and Parhizgar Naser. "Adaptive resources assignment in OFDM-based cognitive radio systems." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 3 (2019): 1935–43. https://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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12

Mach, Pavel, and Robert Bestak. "Radio resources allocation for decentrally controlled relay stations." Wireless Networks 17, no. 1 (2010): 133–48. http://dx.doi.org/10.1007/s11276-010-0269-8.

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Amirsaidov, Ulugbek, and Azamat Qodirov. "Cross-Layer Model of Dynamic Distribution of Radio Resources and Data Flow Service in LTE Networks." International journal of electrical and computer engineering systems 14, no. 1 (2023): 13–19. http://dx.doi.org/10.32985/ijeces.14.1.2.

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In this article, the results of the development of a mathematical model for the time-frequency resource allocation of the uplink channel and flow service in LTE (Long Term Evolution) networks are given. The proposed model is aimed at ensuring the maximum performance of the radio channel and the guaranteed quality of service for data flows of wireless network users. A comparative analysis of the proposed model with the existing methods of the time-frequency resource allocation of the LTE technology is carried out in terms of ensuring the overall performance of the uplink and allocating the requ

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Bouleanu, Iulian, Dorin Alexandrescu, and Mircea Bora. "Radio Frequency Co-Site Management." International conference KNOWLEDGE-BASED ORGANIZATION 21, no. 3 (2015): 660–65. http://dx.doi.org/10.1515/kbo-2015-0112.

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Abstract The radio spectrum is a limited national resource, essential for some governmental applications and increasingly important for a series of non-governmental applications. The allocation of radio resources is done in a centralized manner, designating frequency managers of the defense system structures as local administrators of the resources allotted to the supported echelon. They have a limited number of frequencies they can assign to the emission sources in their area of responsibility. The article addresses the issue of radio spectrum management in the frequency allocation plans when

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15

Shelikhova, T. S., and V. G. Drozdova. "The Analysis of the Usage Efficiency of the Time-frequency Resources for Different 5G NR CORESET Configuration Settings." Herald of the Siberian State University of Telecommunications and Information Science 17, no. 4 (2023): 97–108. http://dx.doi.org/10.55648/1998-6920-2023-17-4-97-108.

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The 5G mobile networks is a New Radio for finding wireless access solutions for Internet access of users with the most demanding requirements for quality service. To implement it radio interface resource allocation functions implemented by hardware and software vendors at base stations must notify subscribers about their decisions with so-called control channels the functions of which are distributed in the CORESET configuration area. The settings of the CORESET parameters affect the efficiency of using radio channel resources. This article discusses CORESET issues and their impact on the effi

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16

Zafar, Ammar, Mohamed-Slim Alouini, Yunfei Chen, and Redha M. Radaydeh. "Optimizing Cooperative Cognitive Radio Networks with Opportunistic Access." Journal of Computer Networks and Communications 2012 (2012): 1–9. http://dx.doi.org/10.1155/2012/294581.

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Optimal resource allocation for cooperative cognitive radio networks with opportunistic access to the licensed spectrum is studied. Resource allocation is based on minimizing the symbol error rate at the receiver. Both the cases of all-participate relaying and selective relaying are considered. The objective function is derived and the constraints are detailed for both scenarios. It is then shown that the objective functions and the constraints are nonlinear and nonconvex functions of the parameters of interest, that is, source and relay powers, symbol time, and sensing time. Therefore, it is

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17

Yin, Han, and Duo Zhang. "Radio Resource Allocation Algorithm Based on Bargaining Game Theory for LTE System." Applied Mechanics and Materials 644-650 (September 2014): 1527–30. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.1527.

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With the rapid development of wireless communication technologies, users could get many kinds of services and applications now. And as the number of users and the amount of traffic are growing, the contradiction between the infinite demand of users and the finite radio resources is getting increasingly apparent. According to this situation, this paper propose a radio resource allocation algorithm based on bargaining game theory for fourth generation long term evolution (LTE) system, with which the network could balance the situations of users in different classes and enhance the utility of use

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18

Bendaoud, Fayssal, Marwen Abdennebi, and Fedoua Didi. "Survey on Scheduling and Radio Resources Allocation in LTE." International Journal of Next-Generation Networks 6, no. 1 (2014): 17–29. http://dx.doi.org/10.5121/ijngn.2014.6102.

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19

Jararweh, Yaser, Mahmoud Al-Ayyoub, Ahmad Doulat, Ahmad Al Abed Al Aziz, Haythem A. Bany Salameh, and Abdallah A. Khreishah. "Software Defined Cognitive Radio Network Framework." International Journal of Grid and High Performance Computing 7, no. 1 (2015): 15–31. http://dx.doi.org/10.4018/ijghpc.2015010102.

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Software defined networking (SDN) provides a novel network resource management framework that overcomes several challenges related to network resources management. On the other hand, Cognitive Radio (CR) technology is a promising paradigm for addressing the spectrum scarcity problem through efficient dynamic spectrum access (DSA). In this paper, the authors introduce a virtualization based SDN resource management framework for cognitive radio networks (CRNs). The framework uses the concept of multilayer hypervisors for efficient resources allocation. It also introduces a semi-decentralized con

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Mounisha, Manuvarthi, V. Krishna Vamsi, Vivek Rajpoot, R. Anil Kumar, and Ramesh K. Verma. "PSO-Based Resource Allocation in Cognitive Radio Ad-Hoc Network." Defence Science Journal 75, no. 3 (2025): 331–38. https://doi.org/10.14429/dsj.20908.

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Increasing demand for spectrum causes the emergence of technologies like Cognitive Radio (CR). Resources like bandwidth and energy are primarily shared by the primary and secondary users in the CR network. Resource utilization depends on the number of nodes, topology dimension, packet generation rate, and time of channel utilization. Therefore, optimizing resources in CR is a need of the hour. In the presented paper, a PSO-based resource allocation scheme is implemented. The input parameters like the number of secondary user nodes, packet generation rate, dimension of the network, and simulati

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Mishra, Mangala Prasad, Sunil Kumar Singh, and Deo Prakash Vidyarthi. "Opportunistic Channel Allocation Model in Collocated Primary Cognitive Network." International Journal of Mathematical, Engineering and Management Sciences 5, no. 5 (2020): 995–1012. http://dx.doi.org/10.33889/ijmems.2020.5.5.076.

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The growing demand of radio spectrum to facilitate the primary/secondary users in a cellular network is a challenging task. Many channel allocation models, applying cognition, have been proposed to increase the radio spectrum utilization. The proposed model peruses three types of users: primary users (PUs), opportunistic primary users (OPUs), and secondary users (SUs) that use the radio resources in collocated primary base stations. Out of these users, the opportunistic primary users and secondary users may request for handover as per their requirements. The objective of the model is to enhanc

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Sabeeh , Saif, and Krzysztof Wesołowski . "On Adaptation of Resources in New Radio Vehicle-to-Everything Mode 1 Dynamic Resource Allocation." Electronics 14, no. 1 (2024): 77. https://doi.org/10.3390/electronics14010077.

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Vehicle-to-Everything (V2X) communication is one of the essential technologies in 5G systems and will certainly play an important role in incoming 6G communications. Two modes of 5G New Radio V2X communication (NR-V2X) have been defined to standardize the direct exchange of messages between vehicles. This paper concentrates on Mode 1, in which message exchange takes place with the support of the cellular infrastructure. In this mode, each vehicle uses a fixed number of subchannels with pre-configured subchannel sizes to transmit packet messages. However, if the packet sizes vary in each transm

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Yasin Ramadhan, Mohamad, Vinsensius Sigit, and Arfianto Fahmi. "Radio Resource Allocation For Device to Device Network Using Auction Algorithm." Jurnal TIARSIE 16, no. 2 (2019): 53. http://dx.doi.org/10.32816/tiarsie.v16i2.52.

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One application of communication from the 5G network in the future is to implement Device to Device (D2D) into heterogeneous multi-tiered communication networks consisting of small cell communications between eNB, cellular and D2D. The application of D2D is useful for the future even though it has several problems with one of them being interference with the frequency of other devices in the same cell. This can affect Quality of Service (QoS) in D2D communication so that it requires the application of a resource allocation distribution that can increase data rate and reduce interference. One o

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Lan, Hai Yan, Hong Tao Song, Yun Long Zhao, and Guo Yin Zhang. "A Resource Allocation Algorithm in RFID System." Advanced Materials Research 694-697 (May 2013): 2462–65. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.2462.

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For problem of limited resources in the RFID (Radio frequency identification) system, a power resource allocation scheme is proposed. The method aims to maximize the system throughput, using cultural algorithm (CA) to search for the optimal power allocation scheme. By dynamically adjusting the signal transmission power of the reader, the overlap area between the reader can be reduced so that the maximum reading range can be obtained. Simulation results show that the algorithm has better performance in the system throughput and energy consumption, reducing the impact of interference between the

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Liu, Xingguang, Li Zhou, Xiaoying Zhang, Xiang Tan, and Jibo Wei. "Joint Radio Map Construction and Dissemination in MEC Networks: A Deep Reinforcement Learning Approach." Wireless Communications and Mobile Computing 2022 (July 19, 2022): 1–12. http://dx.doi.org/10.1155/2022/4621440.

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With the development of 6G, the rapidly increasing number of smart devices deployed in the Industrial Internet of Things (IIoT) environment has been witnessed. The radio environment is showing a trend of complexity, and spectrum conflicts are becoming increasingly acute. User equipment (UE) can accurately sense and utilize spectrum resources through radio map (RM). However, the construction and dissemination of RM incur a heavy computational burden and large dissemination delay, which limit the real-time sensing of spatial spectrum situations. In this paper, we propose an RM construction and d

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Zou, Hong, Min Zhou, Yaping Cui, Peng He, Hong Zhang, and Ruyan Wang. "Service Provisioning in Sliced Cloud Radio Access Networks." Wireless Communications and Mobile Computing 2022 (February 3, 2022): 1–12. http://dx.doi.org/10.1155/2022/7326172.

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Network slicing- (NS-) based cloud radio access networks (C-RANs) have emerged as a key paradigm to support various novel applications in 5G and beyond networks. However, it is still a challenge to allocate resources efficiently due to heterogeneous quality of service (QoS) requirements of diverse services as well as competition among different network slices. In this paper, we consider a service provisioning allocation framework to guarantee resource utilization while ensuring the QoS of users. Specifically, an inter/intraslice bandwidth optimization strategy is developed to maximize the reve

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AlQahtani, Salman Ali. "Towards an Optimal Cloud-Based Resource Management Framework for Next-Generation Internet with Multi-Slice Capabilities." Future Internet 15, no. 10 (2023): 343. http://dx.doi.org/10.3390/fi15100343.

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With the advent of 5G networks, the demand for improved mobile broadband, massive machine-type communication, and ultra-reliable, low-latency communication has surged, enabling a wide array of new applications. A key enabling technology in 5G networks is network slicing, which allows the creation of multiple virtual networks to support various use cases on a unified physical network. However, the limited availability of radio resources in the 5G cloud-Radio Access Network (C-RAN) and the ever-increasing data traffic volume necessitate efficient resource allocation algorithms to ensure quality

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Masmoudi, Ahlem, Kais Mnif, and Faouzi Zarai. "A Survey on Radio Resource Allocation for V2X Communication." Wireless Communications and Mobile Computing 2019 (October 24, 2019): 1–12. http://dx.doi.org/10.1155/2019/2430656.

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Thanks to the deployment of new techniques to support high data rate, high reliability, and QoS provision, Long-Term Evolution (LTE) can be applied for diverse applications. Vehicle-to-everything (V2X) is one of the evolving applications for LTE technology to improve traffic safety, to minimize congestion, and to ensure comfortable driving which requires stringent reliability and latency requirements. As mentioned in the 3rd Generation Partnership Project (3GPP), LTE-based Device-to-Device (D2D) communication is an enabler for V2X services to meet these requirements. Therefore, radio resource

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Mattoo, Mohd Mueen Ul Islam, and Huda Adibah Mohd Ramli. "A study of packet scheduling algorithms in long term evolution-advanced." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 1 (2020): 516. http://dx.doi.org/10.11591/ijeecs.v18.i1.pp516-524.

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<span lang="EN-GB">The allocation of radio resources is one of the most critical functions performed by the Radio Resource Management (RRM) mechanisms in the downlink Long Term Evolution – Advanced (LTE-Advanced). Packet scheduling concerns itself with allocation of these radio resources in an intelligent manner such that system throughput/capacity can be maximized whilst the required multimedia Quality of Service (QoS) is met. Majority of the previous studies of packet scheduling algorithms for LTE-Advanced did not take the effect of channel impairments into account. However, in real wo

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Mohd, Mueen Ul Islam Mattoo, and Adibah Mohd Ramli Huda. "A study of packet scheduling algorithms in long term evolution-advanced." Indonesian Journal of Electrical Engineering and Computer Science (IJEECS) 18, no. 1 (2020): 516–24. https://doi.org/10.11591/ijeecs.v18.i1.pp516-524.

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The allocation of radio resources is one of the most critical functions performed by the Radio Resource Management (RRM) mechanisms in the downlink Long Term Evolution-Advanced (LTE-Advanced). Packet scheduling concerns itself with allocation of these radio resources in an intelligent manner such that system throughput/capacity can be maximized whilst the required multimedia Quality of Service (QoS) is met. Majority of the previous studies of packet scheduling algorithms for LTE-Advanced did not take the effect of channel impairments into account. However, in real world the channel impairments

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Pei-Pei, Chen, Zhang Qin-yu, Wang Ye, and Meng Jing. "Multi-Objective Resources Allocation for OFDM-Based Cognitive Radio Systems." Information Technology Journal 9, no. 3 (2010): 494–99. http://dx.doi.org/10.3923/itj.2010.494.499.

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Mbainaissem, Teubé Cyrille, Abdulfatai Atte Momoh, Déthié Dione, and Paul Python Ndekou. "OPTIMAL ALLOCATION OF RADIO RESOURCES IN A HETEROGENEOUS NETWORK SYSTEM." Advances and Applications in Discrete Mathematics 41, no. 3 (2024): 261–80. http://dx.doi.org/10.17654/0974165824019.

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Shah, Syed Najaf Haider. "SPYDER: QoS-Aware Radio Resource Allocation in Multiuser ISAC-Capable C-V2X Networks." IEEE Open Journal of the Communication Society 6 (April 4, 2025): 3644–63. https://doi.org/10.1109/OJCOMS.2025.3558126.

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Integrated Sensing and Communication (ISAC) in cellular vehicle-to-everything (C-V2X) systems presents a promising solution for enhancing road safety and traffic efficiency. However, it also poses significant challenges in radio resource management, particularly in efficiently allocating time-frequency (TF) resources to meet distinct Quality of Service (QoS) requirements, minimizing resource occupancy for high-resolution radar sensing, and mitigating coordination overhead and interference in a multiuser ISAC-capable C-V2X network. To overcome these challenges, we propose a novel uncoordinated

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Sawant, Rupali, and Shikha Nema. "Outage Analysis in Underlay OFDMA Based Cooperative Cognitive Radio Networks." International Journal of Sensors, Wireless Communications and Control 10, no. 4 (2020): 625–33. http://dx.doi.org/10.2174/2210327910666191218125527.

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Background: Efficient resource allocation in Cooperative Cognitive Radio Network (CCRN) is necessary in order to meet the challenges in future wireless networks. With proper resource allocation, the Quality of Service (QoS) comprising of outage probability and data rate are evaluated in this paper and sufficiently improved with proper subcarrier allocation. Objective: Another important parameter is Signal to Interference Ratio (SIR) which should be above a threshold called minimum protection ratio to maintain the required QoS. Results: The network considered is Orthogonal Frequency Division Mu

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Orike, Sunny, Winner Minah-Eeba, and Nkechinyere Eyidia. "Harvesting cognitive radio networks using artificial intelligence." BOHR Journal of Computational Intelligence and Communication Network 2, no. 1 (2024): 11–17. http://dx.doi.org/10.54646/bjcicn.2024.13.

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The utilization of Artificial Intelligence (AI) in leveraging Cognitive Radio Networks (CRNs) represents an emerging field of study. This surge is primarily driven by operational expenses, concerns over traditional power sources, and limitations inherent in current CRN technologies. Furthermore, integrating AI into CRN operations significantly enhances efficiency and maximizes the application of the electromagnetic spectrum. To enable real-time processing, Cognitive Radio (CR) is paired with AI methodologies, fostering adaptive and intelligent resource allocation. This research paper outlines

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Awoyemi, B. S., B. T. Maharaj, and A. S. Alfa. "Resource Allocation in Heterogeneous Buffered Cognitive Radio Networks." Wireless Communications and Mobile Computing 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/7385627.

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Resources available for operation in cognitive radio networks (CRN) are generally limited, making it imperative for efficient resource allocation (RA) models to be designed for them. However, in most RA designs, a significant limiting factor to the RA’s productivity has hitherto been mostly ignored, the fact that different users or user categories do have different delay tolerance profiles. To address this, in this paper, an appropriate RA model for heterogeneous CRN with delay considerations is developed and analysed. In the model, the demands of users are first categorised and then, based on

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Yang, Guang Long, Xiao Wang, and Xue Zhi Tan. "Power Control Optimization Algorithm in Cognitive Radio Network." Advanced Materials Research 926-930 (May 2014): 3669–72. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.3669.

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For cognitive radio environment needs of different users, A space-time diversity multi-carrier code division multiple access (OFDM-CDMA) technology architecture of the cognitive radio (CR) system is used, a novel non-cooperative power control algorithm and the price game (NPGP), in order to protect the economic interests of the spectrum of network providers, to achieve a fair and efficient allocation of spectrum resources have cognitive and improve spectrum efficiency. Simulation results show that the algorithm under the protection of the economic spectrum premise network provider benefits, bo

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Munir, Rizwan, Yifei Wei, Chao Ma, and Bizhu Yang. "Dynamically Resource Allocation in Beyond 5G (B5G) Network RAN Slicing Using Deep Deterministic Policy Gradient." Wireless Communications and Mobile Computing 2022 (December 21, 2022): 1–13. http://dx.doi.org/10.1155/2022/9958786.

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Network slicing makes it possible for future applications with a variety of adaptability requirements and performance requirements by spliting the physical network into several logical networks. Radio access network (RAN) slicing’s main goal is to assign physical resource blocks (RBs) to mMTC, eMBB, and uRLLC services while ensuring the Quality of service (QoS). Consequently, it is challenging to determine the optimal strategies for 5G radio access network (5G-RAN) slicing because of dynamically changes in slice needs and environmental data, and conventional approaches have difficulty addressi

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Xu, Yang, Kechen Zheng, Xiaoying Liu, Zhao Li, and Jia Liu. "Cognitive Radio Networks: Technologies, Challenges and Applications." Sensors 25, no. 4 (2025): 1011. https://doi.org/10.3390/s25041011.

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In recent years, Cognitive Radio Networks (CRNs) have emerged as a transformative solution to address the growing demand for wireless spectrum resources and the inefficiencies of traditional static spectrum allocation policies [...]

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Yang, Peng, Liao Chen, Hong Zhang, Jing Yang, Ruyan Wang, and Zhidu Li. "Joint Optical and Wireless Resource Allocation for Cooperative Transmission in C-RAN." Sensors 21, no. 1 (2020): 217. http://dx.doi.org/10.3390/s21010217.

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Cooperative multipoint transmission (CoMP) is one of the most promising paradigms for mitigating interference in cloud radio access networks (C-RAN). It allows multiple remote radio units (RRUs) to transmit the same data flow to a user to further improve the signal quality. However, CoMP may incur redundant data transmission over fronthaul network in the C-RAN. In a C-RAN employing CoMP, a key problem is how to coordinate heterogeneous resource allocation to maximize the cooperation gain while reducing the fronthaul load. In this paper, the cooperation transmission based on a multi-dimensional

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Kułacz, Łukasz, and Adrian Kliks. "Dynamic Spectrum Allocation Using Multi-Source Context Information in OpenRAN Networks." Sensors 22, no. 9 (2022): 3515. http://dx.doi.org/10.3390/s22093515.

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Bearing in mind the stringent problem of limited and inefficiently used radio resources, a multi-source mechanism for the dynamic adjustment of occupied frequency bands is proposed. Instead of relying only on radio-related information, the system that collects data from various sources is discussed. Mainly, using the ubiquitous sources of information about the presence of users (such as city monitoring), it is possible to identify areas that have high or low expected traffic with high probabilities. Consequently, in low-traffic areas, it is not necessary to allocate all available spectrum reso

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Trysnyuk, Vasyl, and Volodymyr Ehorov. "Mathematical model of the distribution of radio monitoring resources for observation of satellite communication channels using neural networks." Environmental safety and natural resources 53, no. 1 (2025): 132–38. https://doi.org/10.32347/2411-4049.2025.1.132-138.

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The work is devoted to solving a scientific and practical problem, which consists in developing a mathematical model for distributing radio monitoring equipment for observing satellite communication channels using neural networks. To increase the efficiency of resource allocation, it is proposed to use advanced artificial intelligence algorithms, in particular deep neural networks (DNN), reinforcement learning (RL) and graph neural networks (GNN). The use of such methods allows to significantly increase the adaptability of the system, increase the accuracy of analysis and ensure optimization o

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Wang, Min, Shu Guang Zhang, Qiao Yun Sun, and Yu Zhang. "Resources Allocation Scheme Based on Mode Switch for Multicast Services in MBSFN." Applied Mechanics and Materials 543-547 (March 2014): 3044–48. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.3044.

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The multimedia broadcast and multicast services (MBMS) in 3GPP LTE is characterized by multicast broadcast single frequency network (MBSFN) operation. The multicast services are transmitted by single frequency network (SFN) mode, and the unicast services are delivered with point-to-point (PTP) mode. To avoid the network congestion of the multicast services in MBSFN, a novel resources allocation scheme (RAS) based on mode switch for the multicast services is proposed. The RAS takes advantages of the mode switch between SFN and PTP for the multicast services and minimizes the demanded radio reso

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Ferreira, Lúcio Studer, and Luís M. Correia. "An Efficient and Fair Strategy for Radio Resources Allocation in Multi-radio Wireless Mesh Networks." Wireless Personal Communications 75, no. 2 (2013): 1463–87. http://dx.doi.org/10.1007/s11277-013-1433-0.

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Gharbi, Atef, Abdulsamad Ebrahim Yahya, and Mohamed Ayari. "Comparative Study of Radio Resource Distribution Algorithms." Engineering, Technology & Applied Science Research 14, no. 1 (2024): 13006–11. http://dx.doi.org/10.48084/etasr.6805.

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The equitable distribution of radio resources among different users in wireless networks is a difficult problem and has attracted the interest of many studies. This study presents the Proportional Fair Q-Learning Algorithm (PFLA) to enable the equitable distribution of radio resources among diverse users through the integration of Q-learning and proportional fairness principles. The PFLA, Round Robin (RR), and Max Throughput (MaxTP) algorithms were compared to evaluate their effectiveness in resource allocation. Performance was measured in terms of sum-rate throughputs and fairness index. The

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Syifana, Alfiya, Linda Meylani, and Vinsensius Sigit Widhi Prabowo. "Radio Resource Allocation in D2D Underlay Communication Using Two Phased Auction Based Fair and Interference Resource Allocation." JMECS 8, no. 2 (2021): 1. http://dx.doi.org/10.25124/jmecs.v8i2.3972.

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The high demands of the mobile user will affect the workload of eNodeB, which results in the decreasingperformance system of eNodeB. Device-to-Device (D2D) underlaying communication system is a solution inreducing the workload of eNodeB and increasing the system data rate. This communication system consistsof two users, namely Cellular User Equipment (CUE) and D2D pair, where CUE shares its resources withthe D2D pair. This sharing of resources also causes interference and should be managed using the resourceallocation algorithm. This research used the TAFIRA D2D algorithm and compared it with

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G, Manjula, Pratibha Deshmukh, Udaya Kumar N. L., et al. "Resource Allocation Energy Efficient Algorithm for H-CRAN in 5G." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 3s (2023): 118–26. http://dx.doi.org/10.17762/ijritcc.v11i3s.6172.

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In today's generation, the demand for data rates has also increased due to the rapid surge in the number of users. With this increasing growth, there is a need to develop the next fifth generation network keeping in mind the need to replace the current 4G cellular network. The fifth generation (5G) design in mobile communication technology has been developed keeping in mind all the communication needs of the users. Heterogeneous Cloud Radio Access Network (H-CRAN) has emerged as a capable architecture for the newly emerging network infrastructure for energy efficient networks and high data rat

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Deng, Hongyu, Cheng Wu, and Yiming Wang. "A cognitive gateway-based spectrum sharing method in downlink round robin scheduling of LTE system." Modern Physics Letters B 31, no. 19-21 (2017): 1740070. http://dx.doi.org/10.1142/s021798491740070x.

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A key technique of LTE is how to allocate efficiently the resource of radio spectrum. Traditional Round Robin (RR) scheduling scheme may lead to too many resource residues when allocating resources. When the number of users in the current transmission time interval (TTI) is not the greatest common divisor of resource block groups (RBGs), and such a phenomenon lasts for a long time, the spectrum utilization would be greatly decreased. In this paper, a novel spectrum allocation scheme of cognitive gateway (CG) was proposed, in which the LTE spectrum utilization and CG’s throughput were greatly i

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Feng, Lei, Wenjing Li, Peng Yu, and Xuesong Qiu. "An Enhanced OFDM Resource Allocation Algorithm in C-RAN Based 5G Public Safety Network." Mobile Information Systems 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/9586287.

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Public Safety Network (PSN) is the network for critical communication when disaster occurs. As a key technology in 5G, Cloud-Radio Access Network (C-RAN) can play an important role in PSN instead of LTE-based RAN. This paper firstly introduces C-RAN based PSN architecture and models the OFDM resource allocation problem in C-RAN based PSN as an integer quadratic programming, which allows the trade-off between expected bitrates and allocating fairness of PSN Service User (PSU). However, C-RAN based PSN needs to improve the efficiency of allocating algorithm because of a mass of PSU-RRH associati

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S Manjunatha. "Ra-Csrm: A Federated Learning-Assisted Chaotic Search Resource Mapping for Efficient Qos Aware Spectrum Allocation in Cognitive Radio Networks." Journal of Information Systems Engineering and Management 10, no. 51s (2025): 406–17. https://doi.org/10.52783/jisem.v10i51s.10406.

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Cognitive Radio Networks (CRNs) are emerging as a dynamic solution to the increasing demand for spectrum resources. To enhance Quality of Service (QoS) in CRNs, efficient and fair resource allocation among secondary users (SUs) is imperative, especially in multi-channel environments. Conventional allocation techniques often fail to adapt to rapidly changing network conditions and do not fully address fairness and latency constraints, resulting in suboptimal QoS for SUs. A need exists for a model that ensures low latency, high allocation rates, and fairness in dynamic CRNs. This article introdu

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