Radio Resource Management Based on User and Network Characteristics Considering 5G Radio Access Network in a Metropolitan Environment

2017 ◽  
Vol E100.B (8) ◽  
pp. 1352-1365
Author(s):  
Akira KISHIDA ◽  
Yoshifumi MORIHIRO ◽  
Takahiro ASAI
Keyword(s):  
Resource Management ◽  
Radio Resource Management ◽  
Access Network ◽  
Radio Resource ◽  
Radio Access Network ◽  
Network Characteristics ◽  
Radio Access

Joint radio resource allocation in fog radio access network for healthcare

2018 ◽  
Vol 12 (5) ◽  
pp. 1277-1288 ◽  
Author(s):  
Shiyuan Tong ◽  
Yun Liu ◽  
Hsin-Hung Cho ◽  
Hua-Pei Chiang ◽  
Zhenjiang Zhang
Keyword(s):  
Resource Allocation ◽  
Access Network ◽  
Radio Resource Allocation ◽  
Radio Resource ◽  
Radio Access Network ◽  
Radio Access ◽  
Fog Radio Access Network

scholarly journals Resource Management in Cloud Radio Access Network: Conventional and New Approaches

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2708 ◽  
Author(s):  
Rehenuma Tasnim Rodoshi ◽  
Taewoon Kim ◽  
Wooyeol Choi
Keyword(s):  
Resource Management ◽  
Performance Metrics ◽  
Research Work ◽  
Access Network ◽  
Wireless Sensor ◽  
Research Issues ◽  
Radio Access Network ◽  
Cloud Radio Access Network ◽  
Radio Access ◽  
Management Techniques

Cloud radio access network (C-RAN) is a promising mobile wireless sensor network architecture to address the challenges of ever-increasing mobile data traffic and network costs. C-RAN is a practical solution to the strict energy-constrained wireless sensor nodes, often found in Internet of Things (IoT) applications. Although this architecture can provide energy efficiency and reduce cost, it is a challenging task in C-RAN to utilize the resources efficiently, considering the dynamic real-time environment. Several research works have proposed different methodologies for effective resource management in C-RAN. This study performs a comprehensive survey on the state-of-the-art resource management techniques that have been proposed recently for this architecture. The resource management techniques are categorized into computational resource management (CRM) and radio resource management (RRM) techniques. Then both of the techniques are further classified and analyzed based on the strategies used in the studies. Remote radio head (RRH) clustering schemes used in CRM techniques are discussed extensively. In this research work, the investigated performance metrics and their validation techniques are critically analyzed. Moreover, other important challenges and open research issues for efficient resource management in C-RAN are highlighted to provide future research direction.

scholarly journals Design and Experimental Validation of a Software-Defined Radio Access Network Testbed with Slicing Support

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
K. Koutlia ◽  
R. Ferrús ◽  
E. Coronado ◽  
R. Riggio ◽  
F. Casadevall ◽  
...  
Keyword(s):  
Software Defined Radio ◽  
Radio Channel ◽  
Radio Resource Management ◽  
Access Network ◽  
Network Slicing ◽  
Radio Access Network ◽  
Management Framework ◽  
Radio Access ◽  
Radio Resources ◽  
5G Systems

Network slicing is a fundamental feature of 5G systems to partition a single network into a number of segregated logical networks, each optimized for a particular type of service or dedicated to a particular customer or application. The realization of network slicing is particularly challenging in the Radio Access Network (RAN) part, where multiple slices can be multiplexed over the same radio channel and Radio Resource Management (RRM) functions shall be used to split the cell radio resources and achieve the expected behaviour per slice. In this context, this paper describes the key design and implementation aspects of a Software-Defined RAN (SD-RAN) experimental testbed with slicing support. The testbed has been designed consistently with the slicing capabilities and related management framework established by 3GPP in Release 15. The testbed is used to demonstrate the provisioning of RAN slices (e.g., preparation, commissioning, and activation phases) and the operation of the implemented RRM functionality for slice-aware admission control and scheduling.

scholarly journals Anticipatory QoE Mechanisms in 5G Radio Intelligent Controller

2020 ◽  
Vol 8 (5) ◽  
pp. 2509-2513
Keyword(s):  
Data Collection ◽  
Data Analytics ◽  
Radio Resource Management ◽  
Access Network ◽  
Mobile Video ◽  
Radio Resource ◽  
Intelligent Controller ◽  
Radio Access ◽  
5G Network ◽  
Mobile Video Streaming

3GPP which is working on the 5G specification is also working on the NWDAF (Network Data Analytics Function) which is used for data collection and data analytics in a centralized manner in the 5G Core. ORAN (Open Radio Access Network) is also working on the Radio data collection entities for better handling of the Radio Resource Management which is termed as the Radio Intelligent Controller (RIC). The 5G Network elements and/or the OAM (Operations and Network Management) can decide how to use the data analytics provided by NWDAF and/or the RIC to improve the overall system performance. In this paper we show how to develop anticipatory QoE mechanisms by using the data available at the RIC and the NWDAF. We show that anticipatory AI functionality will help address QoE in a mobile video streaming use case.

Sign in / Sign up

Export Citation Format

Share Document