Wang et al., 2022 - Google Patents
LinkSlice: Fine-grained network slice enforcement based on deep reinforcement learningWang et al., 2022
- Document ID
- 13723984348786371193
- Author
- Wang T
- Chen S
- Zhu Y
- Tang A
- Wang X
- Publication year
- Publication venue
- IEEE Journal on Selected Areas in Communications
External Links
Snippet
Considering network slicing in a cellular network, one of the most intriguing tasks is slice enforcement over air interfaces across multiple cells. The challenges lie in several aspects. First, resources allocated to different slices must achieve soft isolation at the link level …
- 230000002787 reinforcement 0 title abstract description 11
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATIONS NETWORKS
- H04W72/00—Local resource management, e.g. wireless traffic scheduling or selection or allocation of wireless resources
- H04W72/12—Dynamic Wireless traffic scheduling; Dynamically scheduled allocation on shared channel
- H04W72/1205—Schedule definition, set-up or creation
- H04W72/1226—Schedule definition, set-up or creation based on channel quality criteria, e.g. channel state dependent scheduling
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATIONS NETWORKS
- H04W72/00—Local resource management, e.g. wireless traffic scheduling or selection or allocation of wireless resources
- H04W72/12—Dynamic Wireless traffic scheduling; Dynamically scheduled allocation on shared channel
- H04W72/1205—Schedule definition, set-up or creation
- H04W72/1221—Schedule definition, set-up or creation based on age of data to be sent
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance or administration or management of packet switching networks
- H04L41/50—Network service management, i.e. ensuring proper service fulfillment according to an agreement or contract between two parties, e.g. between an IT-provider and a customer
- H04L41/5041—Service implementation
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance or administration or management of packet switching networks
- H04L41/50—Network service management, i.e. ensuring proper service fulfillment according to an agreement or contract between two parties, e.g. between an IT-provider and a customer
- H04L41/5019—Ensuring SLA
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATIONS NETWORKS
- H04W72/00—Local resource management, e.g. wireless traffic scheduling or selection or allocation of wireless resources
- H04W72/04—Wireless resource allocation
- H04W72/0406—Wireless resource allocation involving control information exchange between nodes
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance or administration or management of packet switching networks
- H04L41/50—Network service management, i.e. ensuring proper service fulfillment according to an agreement or contract between two parties, e.g. between an IT-provider and a customer
- H04L41/5003—Managing service level agreement [SLA] or interaction between SLA and quality of service [QoS]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATIONS NETWORKS
- H04W28/00—Network traffic or resource management
- H04W28/16—Central resource management; Negotiation of resources or communication parameters, e.g. negotiating bandwidth or QoS [Quality of Service]
- H04W28/18—Negotiating wireless communication parameters
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/54—Store-and-forward switching systems
- H04L12/56—Packet switching systems
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/02—Details
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATIONS NETWORKS
- H04W28/00—Network traffic or resource management
- H04W28/02—Traffic management, e.g. flow control or congestion control
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic regulation in packet switching networks
- H04L47/70—Admission control or resource allocation
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATIONS NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATIONS NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna systems, i.e. transmission or reception using multiple antennas
- H04B7/022—Site diversity; Macro-diversity
- H04B7/024—Co-operative use of antennas of several sites, e.g. in co-ordinated multipoint or co-operative multiple-input multiple-output [MIMO] systems
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Hua et al. | GAN-powered deep distributional reinforcement learning for resource management in network slicing | |
Mei et al. | Intelligent radio access network slicing for service provisioning in 6G: A hierarchical deep reinforcement learning approach | |
Liang et al. | Deep-learning-based wireless resource allocation with application to vehicular networks | |
Sun et al. | Autonomous resource slicing for virtualized vehicular networks with D2D communications based on deep reinforcement learning | |
Filali et al. | Dynamic SDN-based radio access network slicing with deep reinforcement learning for URLLC and eMBB services | |
Xiang et al. | Mode selection and resource allocation in sliced fog radio access networks: A reinforcement learning approach | |
Deb et al. | Learning-based uplink interference management in 4G LTE cellular systems | |
Wang et al. | LinkSlice: Fine-grained network slice enforcement based on deep reinforcement learning | |
Iacoboaiea et al. | SON coordination in heterogeneous networks: A reinforcement learning framework | |
Zhou et al. | Licensed and unlicensed spectrum allocation in heterogeneous networks | |
Singh et al. | Joint selection of local trainers and resource allocation for federated learning in open RAN intelligent controllers | |
Wang et al. | Online convex optimization for efficient and robust inter-slice radio resource management | |
Liu et al. | Fronthaul-aware software-defined wireless networks: Resource allocation and user scheduling | |
Escudero-Garzás et al. | On the feasibility of 5G slice resource allocation with spectral efficiency: A probabilistic characterization | |
Guerra-Gomez et al. | Machine learning adaptive computational capacity prediction for dynamic resource management in C-RAN | |
Sohaib et al. | Intelligent Resource Management for eMBB and URLLC in 5G and beyond Wireless Networks | |
Fawaz et al. | Cooperation for spreading factor assignment in a multioperator lorawan deployment | |
Lyu et al. | NOMA-assisted on-demand transmissions for monitoring applications in industrial IoT networks | |
Saraiva et al. | Deep reinforcement learning for QoS-constrained resource allocation in multiservice networks | |
Chien et al. | Resource management in 5g mobile networks: Survey and challenges | |
Geng et al. | A reinforcement learning framework for vehicular network routing under peak and average constraints | |
Qazzaz et al. | Machine learning-based xApp for dynamic resource allocation in O-RAN networks | |
Alsenwi et al. | Coexistence of eMBB and URLLC in open radio access networks: A distributed learning framework | |
Marzouk et al. | Highly flexible and traffic isolating ran slicing: A consumer iot-based use case | |
Yan et al. | Deep reinforcement learning based resource allocation for network slicing with massive MIMO |