Fog-Enabled Wireless Communication Networks

  • Yang Yang
  • Xiliang Luo
  • Xiaoli Chu
  • Ming-Tuo Zhou


Wireless communication networks are experiencing an unprecedented traffic growth and an increasing variety of services, each with potentially different traffic patterns and quality of service (QoS) and/or quality of experience (QoE) requirements. To cope with the continuing traffic growth and service expanding, future wireless networks will have to be heterogeneous and densely deployed, featuring the coexistence of different radio access technologies (RATs), and will be significantly more complex to deploy and operate than the existing wireless networks. This has made it evident for the necessity of wireless network self-optimization, where wireless networks are automated to minimize human intervention and to proactively optimize network deployment, operation, and multi-RAT resource allocation to meet increasing service demand from people and the Internet of Things (IoT). Recently, fog computing has been considered as a promising paradigm shift to enable autonomous management and operation of wireless networks. Since research on fog-enabled wireless network self-optimization has just started, there are many aspects that are not well understood and many open challenges that need to be addressed. In this chapter, we explore how fog computing would enable self-optimization for wireless networks, which will act as the infrastructure to provision ubiquitous wireless connectivity for the IoT. More specifically, we will first discuss different self-organizing network (SON) architectures and how they would benefit from the fog computing paradigm, and then look into how fog computing would provide new opportunities and enable new features for several important SON functionalities, including mobility load balancing, self-optimization of mobility robustness and handover, self-coordination of inter-cell interference, self-optimization of coverage and capacity, and self-optimized allocation of computing, storage, and networking resources in wireless networks.


Wireless communication networks Fog computing Self-organizing network Self-optimization Self-coordination Mobility Load balancing Inter-cell interference Resource allocation 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Yang Yang
    • 1
  • Xiliang Luo
    • 1
  • Xiaoli Chu
    • 2
  • Ming-Tuo Zhou
    • 3
  1. 1.Shanghai Institute of Fog Computing Technology (SHIFT), School of Information Science and TechnologyShanghaiTech UniversityShanghaiChina
  2. 2.Department of Electronic & Electrical EngineeringUniversity of SheffieldSheffieldUK
  3. 3.Chinese Academy of Sciences, Shanghai Institute of Microsystem and Information TechnologyShanghaiChina

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