Academic literature on the topic 'Radio access networks, RAN'
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Journal articles on the topic "Radio access networks, RAN":
Saleh, Wardah, and Shahrin Chowdhury. "RANSlicing: Towards Multi-Tenancy in 5G Radio Access Networks." International Journal of Wireless & Mobile Networks 14, no. 2 (April 30, 2022): 43–51. http://dx.doi.org/10.5121/ijwmn.2022.14204.
Wypiór, Dariusz, Mirosław Klinkowski, and Igor Michalski. "Open RAN—Radio Access Network Evolution, Benefits and Market Trends." Applied Sciences 12, no. 1 (January 1, 2022): 408. http://dx.doi.org/10.3390/app12010408.
Dryjański, Marcin, Łukasz Kułacz, and Adrian Kliks. "Toward Modular and Flexible Open RAN Implementations in 6G Networks: Traffic Steering Use Case and O-RAN xApps." Sensors 21, no. 24 (December 7, 2021): 8173. http://dx.doi.org/10.3390/s21248173.
AlQahtani, Salman A. "Cooperative-Aware Radio Resource Allocation Scheme for 5G Network Slicing in Cloud Radio Access Networks." Sensors 23, no. 11 (May 27, 2023): 5111. http://dx.doi.org/10.3390/s23115111.
Gajewski, Sławomir. "Towards 5G — Cloud-based Radio Access Networks." Zeszyty Naukowe Akademii Marynarki Wojennej, no. 3 (September 30, 2017): 1. http://dx.doi.org/10.5604/01.3001.0010.6582.
Iturria-Rivera, Pedro Enrique, Han Zhang, Hao Zhou, Shahram Mollahasani, and Melike Erol-Kantarci. "Multi-Agent Team Learning in Virtualized Open Radio Access Networks (O-RAN)." Sensors 22, no. 14 (July 19, 2022): 5375. http://dx.doi.org/10.3390/s22145375.
Koutlia, K., R. Ferrús, E. Coronado, R. Riggio, F. Casadevall, A. Umbert, and J. Pérez-Romero. "Design and Experimental Validation of a Software-Defined Radio Access Network Testbed with Slicing Support." Wireless Communications and Mobile Computing 2019 (June 12, 2019): 1–17. http://dx.doi.org/10.1155/2019/2361352.
Adrian Kliks, Marcin Dryjanski, Vishnu Ram, Leon Wong, and Paul Harvey. "Towards autonomous open radio access networks." ITU Journal on Future and Evolving Technologies 4, no. 2 (May 17, 2023): 251–68. http://dx.doi.org/10.52953/gjii3746.
Matera, Andrea, Rahif Kassab, Osvaldo Simeone, and Umberto Spagnolini. "Non-Orthogonal eMBB-URLLC Radio Access for Cloud Radio Access Networks with Analog Fronthauling." Entropy 20, no. 9 (September 2, 2018): 661. http://dx.doi.org/10.3390/e20090661.
Zhao, Zixiao, Qinghe Du, Dawei Wang, Xiao Tang, and Houbing Song. "Overview of Prospects for Service-Aware Radio Access towards 6G Networks." Electronics 11, no. 8 (April 16, 2022): 1262. http://dx.doi.org/10.3390/electronics11081262.
Dissertations / Theses on the topic "Radio access networks, RAN":
Schmidt, Robert. "Slicing in heterogeneous software-defined radio access networks." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS525.
5G networks are envisioned to be a paradigm shift towards service-oriented networks. In this thesis, we investigate how to efficiently combine slicing and SD-RAN to provide the required level of flexibility and programmability in the RAN infrastructure to realize service-oriented multi-tenant networks. First, we devise an abstraction of a base station to represent logical base stations and describe a virtualized network service. Second, we propose a novel standard-compliant SD-RAN platform, named FlexRIC, in the form of a software development kit (SDK). Third, we provide a modular design for a slice-aware MAC scheduling framework to efficiently manage and control the radio resources in a multi-service environment with quality-of-service (QoS) support. Finally, we present a dynamic SD-RAN virtualization layer based on the FlexRIC SDK and MAC scheduling framework to flexibly compose a multi-service SD-RAN infrastructure and provide programmability for multiple SD-RAN controllers
Mharsi, Niezi. "Cloud-Radio Access Networks : design, optimization and algorithms." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLT043/document.
Cloud Radio Access Network (C-RAN) has been proposed as a promising architecture to meet the exponential growth in data traffic demands and to overcome the challenges of next generation mobile networks (5G). The main concept of C-RAN is to decouple the BaseBand Units (BBU) and the Remote Radio Heads (RRH), and place the BBUs in common edge data centers (BBU pools) for centralized processing. This gives a number of benefits in terms of cost savings, network capacity improvement and resource utilization gains. However, network operators need to investigate scalable and cost-efficient algorithms for resource allocation problems to enable and facilitate the deployment of C-RAN architecture. Most of these problems are very complex and thus very hard to solve. Hence, we use combinatorial optimization which provides powerful tools to efficiently address these problems.One of the key issues in the deployment of C-RAN is finding the optimal assignment of RRHs (or antennas) to edge data centers (BBUs) when jointly optimizing the fronthaul latency and resource consumption. We model this problem by a mathematical formulation based on an Integer Linear Programming (ILP) approach to provide the optimal strategies for the RRH-BBU assignment problem and we propose also low-complexity heuristic algorithms to rapidly reach good solutions for large problem instances. The optimal RRH-BBU assignment reduces the expected latency and offers resource utilization gains. Such gains can only be achieved when reducing the inter-cell interference caused by the dense deployment of cell sites. We propose an exact mathematical formulation based on Branch-and-Cut methods that enables to consolidate and re-optimize the antennas radii in order to jointly minimize inter-cell interference and guarantee a full network coverage in C-RAN. In addition to the increase of inter-cell interference, the high density of cells in C-RAN increases the amount of baseband processing as well as the amount of data traffic demands between antennas and centralized data centers when strong latency requirements on fronthaul network should be met. Therefore, we discuss in the third part of this thesis how to determine the optimal placement of BBU functions when considering 3GPP split option to find optimal tradeoffs between benefits of centralization in C-RAN and transport requirements. We propose exact and heuristic algorithms based on combinatorial optimization techniques to rapidly provide optimal or near-optimal solutions even for large network sizes
Di, Cicco Nicola. "Scalable Algorithms for Cloud Radio Access Network (C-RAN) Optimization." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23755/.
Thainesh, Joseph S. "Radio access network (RAN) signalling architecture for dense mobile network." Thesis, University of Surrey, 2016. http://epubs.surrey.ac.uk/811126/.
Duan, Jialong. "Coordination inside centralized radio access networks with limited fronthaul capacity." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2017. http://www.theses.fr/2017IMTA0052/document.
Centralized/Cloud Radio Access Network (C-RAN) is a promising mobile network architecture, which can potentially increase the capacity of mobile networks while reducing operators¿ cost and energy consumption. However, the feasibility of C-RAN is limited by the large bit rate requirement in the fronthaul. The objective of this thesis is to improve C-RAN performance while considering fronthaul throughput reduction, fronthaul capacity allocation and users scheduling.We first investigate new functional split architectures between Remote Radio Heads (RRHs) and Baseband Units (BBU) on the uplink to reduce the transmission throughput in fronthaul. Some low layer functions are moved from the BBU to RRHs and a quantitative analysis is provided to illustrate the performance gains. We then focus on Coordinated Multi-point (CoMP) transmissions on the downlink. CoMP can improve spectral efficiency but needs tight coordination between different cells, which is facilitated by C-RAN only if high fronthaul capacity is available. We compare different transmission strategies without and with multi-cell coordination. Simulation results show that CoMP should be preferred for users located in cell edge areas and when fronthaul capacity is high. We propose a hybrid transmission strategy where users are divided into two parts based on statistical Channel State Informations (CSIs). The users located in cell center areas are served by one transmission point with simple coordinated scheduling and those located in cell edge areas are served with CoMP joint transmission. This proposed hybrid transmission strategy offers a good trade-off between users¿ transmission rates and fronthaul capacity cost
Sharara, Mahdi. "Resource Allocation in Future Radio Access Networks." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG024.
This dissertation considers radio and computing resource allocation in future radio access networks and more precisely Cloud Radio Access Network (Cloud-RAN) and Open Radio Access Network (Open-RAN). In these architectures, the baseband processing of multiple base stations is centralized and virtualized. This permits better network optimization and allows for saving capital expenditure and operational expenditure. In the first part, we consider a coordination scheme between radio and computing schedulers. In case the computing resources are not sufficient, the computing scheduler sends feedback to the radio scheduler to update the radio parameters. While this reduces the radio throughput of the user, it guarantees that the frame will be processed at the computing scheduler level. We model this coordination scheme using Integer Linear Programming (ILP) with the objectives of maximizing the total throughput and users' satisfaction. The results demonstrate the ability of this scheme to improve different parameters, including the reduction of wasted transmission power. Then, we propose low-complexity heuristics, and we test them in an environment of multiple services with different requirements. In the second part, we consider the joint radio and computing resource allocation. Radio and computing resources are jointly allocated with the aim of minimizing energy consumption. The problem is modeled as a Mixed Integer Linear Programming Problem (MILP) and is compared to another MILP problem that maximizes the total throughput. The results demonstrate the ability of joint allocation to minimize energy consumption in comparison with the sequential allocation. Finally, we propose a low-complexity matching game-based algorithm that can be an alternative for solving the high-complexity MILP problem. In the last part, we investigate the usage of machine learning tools. First, we consider a deep learning model that aims to learn how to solve the coordination ILP problem, but with a much shorter time. Then, we consider a reinforcement learning model that aims to allocate computing resources for users to maximize the operator's profit
Rabia, Tarek. "Virtualisation des fonctions d'un Cloud Radio Access Network(C-RAN)." Thesis, Sorbonne université, 2018. http://www.theses.fr/2018SORUS009/document.
Over the next five years, the new generation of mobile networks (5G) would face a significant growth of the data volume, exchanged between billions of connected objects and applications. Furthermore, the emergence of new technologies, such as Internet of Things (IoT), autonomous driving and augmented reality, imposes higher performance and quality of service (QoS) requirements. Meeting these requirements, while reducing the Capital and Operation Expenditures (CAPEX/OPEX), are the pursued goals of the mobile operators. Consequently, Telcos define a new radio access architecture, called Cloud Radio Access Network (C-RAN). The C-RAN principle is to centralize, within a pool, the processing unit of a radio interface, named BaseBand Unit (BBU). These two units are interconnected through a Fronthaul (FH) network. In this thesis, we design a new partially centralized C-RAN architecture that integrates a virtualization platform, based on a Xen environment, called Metamorphic Network (MNet). Through this architecture, we aim to: i) implement a pool in which physical resources (processors, memory, network ports, etc.) are shared between virtualized BBUs and other applications; ii) establish an open FH network that can be used by multiple operators, service providers and third parties to deploy their services and Apps closer to the users for a better Quality of Experience (QoE); iii) exploit, through the FH, the existing Ethernet infrastructures to reduce CAPEX/OPEX; and finally iv) provide the recommended network performance for the 5G. In the first contribution, we define a new Xen architecture for the MNet platform integrating the packet-processing framework, OpenDataPlane (ODP), within a privileged Xen domain, called Driver Domain (DD). This new architecture accelerates the data packet processing within MNet, while avoiding the physical CPUs overuse by ODP. Thus, virtual CPU cores (vCPU) are allocated within DD and are used by ODP to accelerate the packet processing. This new Xen architecture improves the MNet platform by 15%. In the second contribution, we implement two network solutions within the FH. The first solution consist of deploying a layer 2 network protocol, Transparent Interconnection of Lots of Links (TRILL), to connect multiple elements of our C-RAN architecture. The second solution consists of implementing a Software Defined Network (SDN) model managed by Open Network Operating System (ONOS), a distributed SDN controller that is which is virtualized within BBU pool. Moreover, a network performance comparison is performed between these two solutions
Rabia, Tarek. "Virtualisation des fonctions d'un Cloud Radio Access Network(C-RAN)." Electronic Thesis or Diss., Sorbonne université, 2018. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2018SORUS009.pdf.
Over the next five years, the new generation of mobile networks (5G) would face a significant growth of the data volume, exchanged between billions of connected objects and applications. Furthermore, the emergence of new technologies, such as Internet of Things (IoT), autonomous driving and augmented reality, imposes higher performance and quality of service (QoS) requirements. Meeting these requirements, while reducing the Capital and Operation Expenditures (CAPEX/OPEX), are the pursued goals of the mobile operators. Consequently, Telcos define a new radio access architecture, called Cloud Radio Access Network (C-RAN). The C-RAN principle is to centralize, within a pool, the processing unit of a radio interface, named BaseBand Unit (BBU). These two units are interconnected through a Fronthaul (FH) network. In this thesis, we design a new partially centralized C-RAN architecture that integrates a virtualization platform, based on a Xen environment, called Metamorphic Network (MNet). Through this architecture, we aim to: i) implement a pool in which physical resources (processors, memory, network ports, etc.) are shared between virtualized BBUs and other applications; ii) establish an open FH network that can be used by multiple operators, service providers and third parties to deploy their services and Apps closer to the users for a better Quality of Experience (QoE); iii) exploit, through the FH, the existing Ethernet infrastructures to reduce CAPEX/OPEX; and finally iv) provide the recommended network performance for the 5G. In the first contribution, we define a new Xen architecture for the MNet platform integrating the packet-processing framework, OpenDataPlane (ODP), within a privileged Xen domain, called Driver Domain (DD). This new architecture accelerates the data packet processing within MNet, while avoiding the physical CPUs overuse by ODP. Thus, virtual CPU cores (vCPU) are allocated within DD and are used by ODP to accelerate the packet processing. This new Xen architecture improves the MNet platform by 15%. In the second contribution, we implement two network solutions within the FH. The first solution consist of deploying a layer 2 network protocol, Transparent Interconnection of Lots of Links (TRILL), to connect multiple elements of our C-RAN architecture. The second solution consists of implementing a Software Defined Network (SDN) model managed by Open Network Operating System (ONOS), a distributed SDN controller that is which is virtualized within BBU pool. Moreover, a network performance comparison is performed between these two solutions
Mharsi, Niezi. "Cloud-Radio Access Networks : design, optimization and algorithms." Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLT043.
Cloud Radio Access Network (C-RAN) has been proposed as a promising architecture to meet the exponential growth in data traffic demands and to overcome the challenges of next generation mobile networks (5G). The main concept of C-RAN is to decouple the BaseBand Units (BBU) and the Remote Radio Heads (RRH), and place the BBUs in common edge data centers (BBU pools) for centralized processing. This gives a number of benefits in terms of cost savings, network capacity improvement and resource utilization gains. However, network operators need to investigate scalable and cost-efficient algorithms for resource allocation problems to enable and facilitate the deployment of C-RAN architecture. Most of these problems are very complex and thus very hard to solve. Hence, we use combinatorial optimization which provides powerful tools to efficiently address these problems.One of the key issues in the deployment of C-RAN is finding the optimal assignment of RRHs (or antennas) to edge data centers (BBUs) when jointly optimizing the fronthaul latency and resource consumption. We model this problem by a mathematical formulation based on an Integer Linear Programming (ILP) approach to provide the optimal strategies for the RRH-BBU assignment problem and we propose also low-complexity heuristic algorithms to rapidly reach good solutions for large problem instances. The optimal RRH-BBU assignment reduces the expected latency and offers resource utilization gains. Such gains can only be achieved when reducing the inter-cell interference caused by the dense deployment of cell sites. We propose an exact mathematical formulation based on Branch-and-Cut methods that enables to consolidate and re-optimize the antennas radii in order to jointly minimize inter-cell interference and guarantee a full network coverage in C-RAN. In addition to the increase of inter-cell interference, the high density of cells in C-RAN increases the amount of baseband processing as well as the amount of data traffic demands between antennas and centralized data centers when strong latency requirements on fronthaul network should be met. Therefore, we discuss in the third part of this thesis how to determine the optimal placement of BBU functions when considering 3GPP split option to find optimal tradeoffs between benefits of centralization in C-RAN and transport requirements. We propose exact and heuristic algorithms based on combinatorial optimization techniques to rapidly provide optimal or near-optimal solutions even for large network sizes
Morcos, Mira. "Auction-based dynamic resource orchestration in cloud-based radio access networks." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLL003.
Network densification using small cells massively deployed over the macro-cell areas, represents a promising solution for future 5G mobile networks to cope with mobile traffic increase. In order to simplify the management of the heterogeneous Radio Access Network (RAN) that results from the massive deployment of small cells, recent research and industrial studies have promoted the design of novel centralized RAN architectures termed as Cloud-RAN (C-RAN), or Virtual RAN (V-RAN), by incorporating the benefits of cloud computing and Network Functions Virtualization (NFV). The DynaRoC project aims at (1) developing a theoretical framework of resource orchestration for C-RAN and deriving the fundamental performance limits as well as the tradeoffs among various system parameters, and (2) designing dynamic resource orchestration mechanisms based on the theoretical findings to achieve a desired performance balance, by taking into account various design challenges. The PhD student will investigate innovative resource optimization mechanisms to foster the deployment of C-RANs, improving their performance exploiting the enabling Network Functions Virtualization technology
Books on the topic "Radio access networks, RAN":
Peng, Mugen, Zhongyuan Zhao, and Yaohua Sun. Fog Radio Access Networks (F-RAN). Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50735-0.
Quek, Tony Q. S., Mugen Peng, Osvaldo Simeone, and Wei Yu, eds. Cloud Radio Access Networks. Cambridge: Cambridge University Press, 2016. http://dx.doi.org/10.1017/9781316529669.
Venkatarman, Hrishikesh, and Ramona Trestian. 5G Radio Access Networks. 6000 Broken Sound Parkway NW, Suite 300 Boca Raton, FL 33487-2742: CRC Press, 2017. http://dx.doi.org/10.1201/9781315230870.
Zhang, Ying-Jun Angela, Congmin Fan, and Xiaojun Yuan. Scalable Signal Processing in Cloud Radio Access Networks. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-15884-2.
Matin, Mohammad A., ed. Spectrum Access and Management for Cognitive Radio Networks. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-2254-8.
Berlemann, Lars. Cognitive radio for dynamic spectrum access. Hoboken, NJ: J. Wiley & Sons, 2009.
Hossain, Ekram. Dynamic spectrum access and management in cognitive radio networks. Cambridge: Cambridge University Press, 2009.
Calhoun, George. Wireless access and the local telephone network. Boston: Artech House, 1992.
Wu, Leijia. A Study on Radio Access Technology Selection Algorithms. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (2nd 2007 Dublin, Ireland). 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks. Piscataway, NJ: IEEE, 2007.
Book chapters on the topic "Radio access networks, RAN":
Li, Xi. "Dimensioning for Multi-Iub RAN Scenario." In Radio Access Network Dimensioning for 3G UMTS, 203–45. Wiesbaden: Vieweg+Teubner, 2011. http://dx.doi.org/10.1007/978-3-8348-8111-3_8.
Frauendorf, José Luiz, and Érika Almeida de Souza. "The Evolution of RAN (Radio Access Network), D-RAN, C-RAN, V-RAN, and O-RAN." In The Architectural and Technological Revolution of 5G, 139–54. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-10650-7_10.
He, Wencheng, Jinjin Gong, Xin Su, Jie Zeng, Xibin Xu, and Limin Xiao. "SDN-Enabled C-RAN? An Intelligent Radio Access Network Architecture." In New Advances in Information Systems and Technologies, 311–16. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31307-8_32.
Tang, Shaoxian, Zhifeng Zhang, Jun Wu, and Hui Zhu. "FPGA-Based Turbo Decoder Hardware Accelerator in Cloud Radio Access Network (C-RAN)." In Communications and Networking, 211–20. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66625-9_21.
Naghian, Siamäk, and Heikki Kaaranen. "UMTS Radio Access Network." In UMTS Networks, 99–142. Chichester, UK: John Wiley & Sons, Ltd, 2005. http://dx.doi.org/10.1002/047001105x.ch5.
Vaezi, Mojtaba, and Ying Zhang. "Radio Access Network Evolution." In Wireless Networks, 67–86. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54496-0_6.
Xiang, Jie, Yan Zhang, and Tor Skeie. "Dynamic Spectrum Sharing in Cognitive Radio Femtocell Networks." In Access Networks, 164–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11664-3_13.
Salous, Sana, Thomas Werthmann, Ghassan Dahman, Jose Flordelis, Michael Peter, Sooyoung Hur, Jeongho Jh Park, Denis Rose, and Andrés Navarro. "Urban Radio Access Networks." In Cooperative Radio Communications for Green Smart Environments, 17–69. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003337720-2.
Lang, Ke, Yuan Wu, and Danny H. K. Tsang. "How to Optimally Schedule Cooperative Spectrum Sensing in Cognitive Radio Networks." In Access Networks, 133–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11664-3_11.
Ma, Miao, and Danny H. K. Tsang. "Efficient Spectrum Sharing in Cognitive Radio Networks with Implicit Power Control." In Access Networks, 149–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11664-3_12.
Conference papers on the topic "Radio access networks, RAN":
Barth, Ulrich. "Self-X RAN: Autonomous self organizing radio access networks." In 2009 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks - WiOpt 2009. IEEE, 2009. http://dx.doi.org/10.1109/wiopt.2009.5291558.
Nakazawa, Masataka. "Photonics for next generation radio access network (RAN)." In XXXVth URSI General Assembly and Scientific Symposium. Gent, Belgium: URSI – International Union of Radio Science, 2023. http://dx.doi.org/10.46620/ursigass.2023.3778.vihk3599.
Cai, Yegui, F. Richard Yu, and Shengrong Bu. "Cloud radio access networks (C-RAN) in mobile cloud computing systems." In IEEE INFOCOM 2014 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). IEEE, 2014. http://dx.doi.org/10.1109/infcomw.2014.6849260.
Hsu, Ching-Kuo, Jia-Ming Liang, Kun-Ru Wu, Jen-Jee Chen, and Yu-Chee Tseng. "Energy-Efficient Dynamic Point Selection for Cloud Radio Access Networks (C-RAN)." In 2017 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2017. http://dx.doi.org/10.1109/wcnc.2017.7925554.
Dandachi, Ghina, Tijani Chahed, Salah Eddine Elayoubi, Nada Chendeb Taher, and Ziad Fawal. "Joint allocation strategies for radio and processing resources in Virtual Radio Access Networks (V-RAN)." In 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC). IEEE, 2017. http://dx.doi.org/10.1109/pimrc.2017.8292512.
Fonseca, Felipe Freitas, Sand Luz Correa, and Kleber Vieira Cardoso. "Optimizing allocation and positioning in a disaggregated radio access network." In XXXVII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/sbrc.2019.7403.
Hsu, Ching-Kuo, Jia-Ming Liang, Jen-Jee Chen, Kun-Ru Wu, and Yu-Chee Tseng. "Data offloading for dynamic point selection in cloud radio access networks (C-RAN)." In 2018 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2018. http://dx.doi.org/10.1109/wcnc.2018.8377006.
Ojaghi, Behnam, Ferran Adelantado, Elli Kartsakli, Angelos Antonopoulos, and Christos Verikoukis. "Sliced-RAN: Joint Slicing and Functional Split in Future 5G Radio Access Networks." In ICC 2019 - 2019 IEEE International Conference on Communications (ICC). IEEE, 2019. http://dx.doi.org/10.1109/icc.2019.8761081.
Restuccia, Francesco, Erik Blasch, Andrew Ashdown, Jonathan Ashdown, and Kurt Turck. "3D-O-RAN: Dynamic Data Driven Open Radio Access Network Systems." In MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM). IEEE, 2022. http://dx.doi.org/10.1109/milcom55135.2022.10017706.
Ying Li, Jianzhong Charlie Zhang, and Mian Dong. "Smart Grid in radio access networks (SG-RAN): Smart energy management at cell-sites." In 2014 IEEE 11th Consumer Communications and Networking Conference (CCNC). IEEE, 2014. http://dx.doi.org/10.1109/ccnc.2014.6866546.
Reports on the topic "Radio access networks, RAN":
DEFENSE SCIENCE BOARD WASHINGTON DC. Wideband Radio Frequency Modulation: Dynamic Access to Mobile Information Networks. Fort Belvoir, VA: Defense Technical Information Center, July 2003. http://dx.doi.org/10.21236/ada417214.
Tang, Zhenyu, and J. J. Garcia-Luna-Aceves. Hop Reservation Multiple Access (HRMA) for Multichannel Packet Radio Networks. Fort Belvoir, VA: Defense Technical Information Center, January 1998. http://dx.doi.org/10.21236/ada461856.
Georgiopoulos, Michael, and P. Papantoni-Kazakos. A Random Access Algorithm for Frequency Hopped Spread Spectrum Packet Radio Networks. Fort Belvoir, VA: Defense Technical Information Center, March 1986. http://dx.doi.org/10.21236/ada165935.
Wieselthier, Jeffrey E., and Anthony Ephremides. A Study of Channel-Access Schemes for Integrated Voice/Data Radio Networks. Fort Belvoir, VA: Defense Technical Information Center, November 1991. http://dx.doi.org/10.21236/ada243584.
Stevens, James A. Spatial Reuse through Dynamic Power and Routing Control in Common-Channel Random-Access Packet Radio Networks. Fort Belvoir, VA: Defense Technical Information Center, August 1988. http://dx.doi.org/10.21236/ada197898.
DEFENSE SCIENCE BOARD WASHINGTON DC. Report of the Defense Science Board Task Force on Wideband Radio Frequency Modulation: Dynamic Access to Mobile Information Networks. Fort Belvoir, VA: Defense Technical Information Center, July 2003. http://dx.doi.org/10.21236/ada428978.
McGarrigle, Malachy. Watchpoints for Consideration When Utilising a VDI Network to Teach Archicad BIM Software Within an Educational Programme. Unitec ePress, October 2023. http://dx.doi.org/10.34074/ocds.099.