Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top

2020 | Book

Brief Introduction of Fog Radio Access Networks Read chapter Read first chapter

Fog Radio Access Networks (F-RAN)

Architectures, Technologies, and Applications

Authors: Prof. Mugen Peng, Dr. Zhongyuan Zhao, Dr. Yaohua Sun

Publisher: Springer International Publishing

Book Series : Wireless Networks

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

Login to get access
insite
SEARCH

About this book

This book provides a comprehensive introduction of Fog Radio Access Networks (F-RANs), from both academic and industry perspectives. The authors first introduce the network architecture and the frameworks of network management and resource allocation for F-RANs. They then discuss the recent academic research achievements of F-RANs, such as the analytical results of theoretical performance limits and optimization theory-based resource allocation techniques. Meanwhile, they discuss the application and implementations of F-RANs, including the latest standardization procedure, and the prototype and test bed design. The book is concluded by summarizing the existing open issues and future trends of F-RANs.

Includes the latest theoretical and technological research achievements of F-RANs, also discussing existing open issues and future trends of F-RANs toward 6G from an interdisciplinary perspective; Provides commonly-used tools for research and development of F-RANs such as open resource projects for implementing prototypes and test beds;Includes examples of prototype and test bed design and gives tools to evaluate the performance of F-RANs in simulations and experimental circumstances.

Table of Contents

Frontmatter
Chapter 1. Brief Introduction of Fog Radio Access Networks
Abstract
To meet diverse performance requirements of the fifth generation (5G) and even the sixth generation (6G) mobile communication systems, fog radio access network (F-RAN) has been proposed to improve capacity, decrease transmit latency, and increase connective density through combining cloud computing, mobile edge computing (MEC) into heterogeneous networks (HetNets). In this section, we will review the evolution motivation and path of radio access networks and present the potential emerging services over F-RANs. Since F-RANs are strictly related to MEC and cloud computing, the difference among them will be highlighted. With the rapid deployment of 5G, 6G has attracted extensive attentions from academia, industry, and government agencies, and the features and key techniques of F-RANs in 6G will be discussed as well.
Mugen Peng, Zhongyuan Zhao, Yaohua Sun
Chapter 2. System Architecture of Fog Radio Access Networks
Abstract
As a promising architecture, the fog radio access network (F-RAN) can achieve high spectrum efficiency, energy efficiency, and low-latency by leveraging edge computing, cloud computing, and heterogenous networking. To fully unleash the potentials of F-RANs, in this chapter, a comprehensive overview of system architecture of F-RANs is provided. Specifically, the traditional system architecture of F-RANs is first introduced, which features a cloud computing layer, a network access layer, a logical fog layer, and a terminal layer. Then, network slicing in F-RANs for 5G is discussed to flexibly provide a soft-defined networking in a cost-efficient way. As for the radio interface, non-orthogonal multiple access, interference control, and transmission mode selection are identified as three key techniques. Later on, several application cases are demonstrated, including F-RAN enabled vehicles-to-anything communication, F-RAN enabled space communication, and so on. Finally, motivated by the recent advances in artificial intelligence (AI), F-RANs are anticipated to evolve towards an AI-driven paradigm with a glance at the corresponding architecture, principles, and open issues.
Mugen Peng, Zhongyuan Zhao, Yaohua Sun
Chapter 3. Theoretical Performance Analysis of Fog Radio Access Networks
Abstract
The theoretical performance analysis results of F-RANs will be provided in this section. First, we will studied the information-theoretical performance. The conventional information-theoretical performance metrics are not applicable since they cannot capture the computation and caching capabilities of F-RANs. To solve this problem, we firstly formulate a system model to characterize the coordination of caching and computing between the cloud and fog-computing layers in F-RANs. Then, some analytical results, such as effective capacity and latency, are derived to figure out the performance limits of F-RANs and provide some insights for the system design. These research methodology analytical results can be extended into the content centric networks and mobile edge computing systems.
Mugen Peng, Zhongyuan Zhao, Yaohua Sun
Chapter 4. Cooperative Signal Processing in Fog Radio Access Networks
Abstract
In this chapter, we will discuss the cooperative signal processing technique in F-RANs, which is a key enabler to boost F-RAN capacity. First, cooperative non-orthogonal multiple access (NOMA) is presented aiming at further improving user data rate compared to traditional orthogonal multiple access and NOMA schemes. Second, as an effective tool to handle information asymmetry, contract theory is involved and the interference mitigation between the macrocell and remote radio heads (RRHs) is formulated as a contract design problem, in which RRHs can use cooperative signal processing to help the macrocell serve its user. By simulation, the effectiveness of cooperative NOMA and contract based cooperative signal processing deign is confirmed.
Mugen Peng, Zhongyuan Zhao, Yaohua Sun
Chapter 5. Flexible Network Management in Fog Radio Access Networks
Abstract
In F-RANs, flexible and adaptive network management mechanisms should be employed to improve network operation efficiency. In this chapter, network management in F-RANs is presented by involving the concept of network slicing. In particular, a paradigm, named as access slicing, will be firstly introduced. Then, resource orchestration in F-RANs will be optimized considering diversified service requirements.
Mugen Peng, Zhongyuan Zhao, Yaohua Sun
Chapter 6. Dynamic Resource Allocation in Fog Radio Access Networks
Abstract
To improve the transmission efficiency and support the requirements of quality of services (QoS), the optimization of resource allocation in F-RANs will be introduced in this chapter. To implement centralized resource allocation at the cloud computing layer in F-RANs, the joint optimization algorithms can be designed based on the convex optimization and mixed-integer nonlinear programming theory. Meanwhile, cooperative game theory-based methods can be used to support distributed coordinated resource allocation mechanism in the fog computing layer. Finally, a deep reinforcement learning-based method is introduced to implement online resource allocation, which can keep pace with high dynamics of transmission circumstances in F-RANs.
Mugen Peng, Zhongyuan Zhao, Yaohua Sun
Chapter 7. Content Caching in Fog Radio Access Networks
Abstract
In F-RANs, content caches are deployed at both the cloud and fog computing layers to keep the popular content objects at the edge of networks. Therefore, a part of user requests can be responded immediately without multi-hop routing, and the QoS guarantee can be improved significantly. In this chapter, we will firstly introduce the hierarchical cooperative caching framework in F-RANs. Next, the content delivery schemes in F-RANs will be introduced, where the content pushing procedure will be considered as well. Finally, the joint optimization of caching and radio resources will be studied to improve the utility and reduce the cost of content caching.
Mugen Peng, Zhongyuan Zhao, Yaohua Sun
Chapter 8. Computation Offloading in Fog Radio Access Networks
Abstract
Since sufficient computation resource can be provided in F-RANs, a concept named computation offloading is proposed to speed up the execution of computation tasks by moving the processing procedure from the users to more powerful nodes via wireless transmissions. In this chapter, several offloading strategies will be introduced due to different execution requirements of computation applications. Next, the optimization of offloading decisions will be discussed to keep a sophisticated tradeoff between the offloading costs and the processing efficiency.
Mugen Peng, Zhongyuan Zhao, Yaohua Sun
Chapter 9. Prototype Design of Fog Radio Access Networks
Abstract
To facilitate various performance verification in practical fog radio access networks (F-RANs), this chapter will have a discussion on the prototype and test bed design of F-RANs. First, the design basics of F-RAN prototypes are elaborated, which are about fog computing enablers and the network controller. Second, some commonly used development tools will be presented to provide convenience for implementing F-RAN prototypes. Next, an example F-RAN prototype will be demonstrated, on which experimental evaluation is conducted to confirm the superior performance gains brought by F-RANs.
Mugen Peng, Zhongyuan Zhao, Yaohua Sun
Chapter 10. Future Trends and Open Issues in Fog Radio Access Networks
Abstract
Recently, the research and development of 6G have been triggered, and new enabling techniques and novel applications are emerging. Although the paradigm of F-RANs has great potential to be compatible with these techniques and applications, there still exist some critical issues. To support AI-enabled wireless services, which are the mainstreams, network intelligence should be implemented in the future F-RANs. As distributively cooperative learning paradigms, federated learning can be used to implement intelligent processing and management, which can fully explore the potential of fog computing capability in F-RANs. In this chapter, we will firstly discuss the future trends of F-RANs, especially the combination of AI and F-RANs in 6G systems. Then, a federated learning-based paradigm of intelligent of F-RANs will be provided, and the key enabling techniques will be discussed as well. Finally, the existing open issues of F-RANs will be introduced, from both the academic and industrial perspectives.
Mugen Peng, Zhongyuan Zhao, Yaohua Sun
Backmatter
Metadata
Title
Fog Radio Access Networks (F-RAN)
Authors
Prof. Mugen Peng
Dr. Zhongyuan Zhao
Dr. Yaohua Sun
Copyright Year
2020
Electronic ISBN
978-3-030-50735-0
Print ISBN
978-3-030-50734-3
DOI
https://doi.org/10.1007/978-3-030-50735-0

Premium Partner

    Image Credits