scholarly journals A Cloud RAN Architecture for LoRa

2020 ◽  
Author(s):  
Christophe Delacourt ◽  
Patrick Savelli ◽  
Vincent Savaux
Keyword(s):  
Performance Indicator ◽  
Access Network ◽  
The Other ◽  
Analog To Digital ◽  
Cloud Radio Access Network ◽  
Radio Access ◽  
Analog To Digital Conversion ◽  
Analog Part ◽  
Network Functions ◽  
Cloud Ran

This paper deals with a cloud radio access network (CRAN)<br>architecture for the LoRa system. In the suggested design,<br>the gateway embeds a limited remote radio head (RRH),<br>including the analog radio-frequency (RF) analog part, the<br>digital-to-analog and analog-to-digital conversion, and a<br>digital front-end (DFE). The other LoRa network functions,<br>including the physical (PHY) layer, the LoRaWAN medium<br>access control (MAC) layer, and the application and customer<br>servers are implemented as cloud resources. The<br>presented approach leads to a flexible RAN that is robust<br>to the variations of capacity needs. Furthermore, it allows<br>us to test very specific LoRa features, such as the detection<br>or demodulation, while bypassing the other ones including<br>the hardware RRH. The methodology and tools we<br>used to deploy a LoRa cloud RAN are detailed, and results<br>concerning the performance indicator (CPU load, memory<br>consumption) are provided as well.

scholarly journals A Cloud RAN Architecture for LoRa

2020 ◽  
Author(s):  
Christophe Delacourt ◽  
Patrick Savelli ◽  
Vincent Savaux
Keyword(s):  
Performance Indicator ◽  
Access Network ◽  
The Other ◽  
Analog To Digital ◽  
Cloud Radio Access Network ◽  
Radio Access ◽  
Analog To Digital Conversion ◽  
Analog Part ◽  
Network Functions ◽  
Cloud Ran

This paper deals with a cloud radio access network (CRAN)<br>architecture for the LoRa system. In the suggested design,<br>the gateway embeds a limited remote radio head (RRH),<br>including the analog radio-frequency (RF) analog part, the<br>digital-to-analog and analog-to-digital conversion, and a<br>digital front-end (DFE). The other LoRa network functions,<br>including the physical (PHY) layer, the LoRaWAN medium<br>access control (MAC) layer, and the application and customer<br>servers are implemented as cloud resources. The<br>presented approach leads to a flexible RAN that is robust<br>to the variations of capacity needs. Furthermore, it allows<br>us to test very specific LoRa features, such as the detection<br>or demodulation, while bypassing the other ones including<br>the hardware RRH. The methodology and tools we<br>used to deploy a LoRa cloud RAN are detailed, and results<br>concerning the performance indicator (CPU load, memory<br>consumption) are provided as well.

scholarly journals Fronthaul for Cloud-RAN Enabling Network Slicing in 5G Mobile Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Line M. P. Larsen ◽  
Michael S. Berger ◽  
Henrik L. Christiansen
Keyword(s):  
Mobile Networks ◽  
Network Architecture ◽  
Network Virtualization ◽  
Access Network ◽  
Network Slicing ◽  
Cloud Radio Access Network ◽  
Radio Access ◽  
A Minor ◽  
Cloud Ran ◽  
5G Mobile Networks

This work considers how network slicing can use the network architecture Cloud-Radio Access Network (C-RAN) as an enabler for the required prerequisite network virtualization. Specifically this work looks at a segment of the C-RAN architecture called the fronthaul network. The fronthaul network required for network slicing needs to be able to dynamically assign capacity where it is needed. Deploying a fronthaul network faces a trade-off between fronthaul bitrate, flexibility, and complexity of the local equipment close to the user. This work relates the challenges currently faced in C-RAN research to the network requirements in network slicing. It also shows how using a packet-switched fronthaul for network slicing will bring great advantages and enable the use of different functional splits, while the price to pay is a minor decrease in fronthaul length due to latency constraints.

scholarly journals Energy-Effective Power Control Algorithm with Mobility Prediction for 5G Heterogeneous Cloud Radio Access Network

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2904 ◽  
Author(s):  
Hyebin Park ◽  
Yujin Lim
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Control Algorithm ◽  
Access Network ◽  
Mobility Prediction ◽  
Switching Operation ◽  
Cloud Radio Access Network ◽  
Radio Access ◽  
Power Control Algorithm ◽  
Heterogeneous Cloud

In 5G networks, heterogeneous cloud radio access network (H-CRAN) is considered a promising future architecture to minimize energy consumption and efficiently allocate resources. However, with the increase in the number of users, studies are performed to overcome the energy consumption problems. In this study, we propose a power control algorithm with mobility prediction to provide a high-energy efficiency for 5G H-CRAN. In particular, the proposed algorithm predicts UE mobility in vehicular mobility scenarios and performs remote radio head (RRH) switching operations based on % prediction results. We formulate an optimization problem to maximize the energy efficiency while satisfying the outage probability requirement. We then propose an RRH switching operation based on Markov mobility prediction and optimize the transmission power based on a gradient method. Simulation results demonstrate the improved energy efficiency compared with those of existing RRH switching-operation algorithms.

Robust Multigroup Multicast Beamforming Design for Backhaul-Limited Cloud Radio Access Network

2019 ◽  
Vol 26 (1) ◽  
pp. 189-193 ◽  
Author(s):  
Yiyun Chen ◽  
Shiwen He ◽  
Yongming Huang ◽  
Ju Ren ◽  
Luxi Yang
Keyword(s):  
Access Network ◽  
Radio Access Network ◽  
Cloud Radio Access Network ◽  
Radio Access ◽  
Multicast Beamforming

scholarly journals SDR Enabled C-RAN Implementation using OpenAirInterface

2021 ◽  
Author(s):  
Akeem Olapade Mufutau ◽  
Fernando Pedro Guiomar ◽  
Arnaldo Oliveira ◽  
Paulo Pereira Monteiro
Keyword(s):  
Open Source ◽  
Software Defined Radio ◽  
Cellular Network ◽  
Access Network ◽  
Mobile Network ◽  
Radio Access Network ◽  
Research Activities ◽  
Radio Access ◽  
Continuous Dynamic ◽  
Cloud Ran

Abstract Towards enabling 5G radio access technologies and beyond to meet the requirements for continuous dynamic and diverse services, flexibility and scalability of the cellular network are therefore pertinent. The utilization of software-defined radio (SDR) aided with an open-source platform and virtualization techniques are increasingly exposing the realization of desirable flexibility for radio access network (RAN) while enabling the development of a prototype which can be directed at fostering further mobile network research activities. In this paper, we review OpenAirInterface (OAI) implementation and present an OAI based cloud RAN (C-RAN) testbed with which mobile fronthaul (MFH) solutions can be tested.

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