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Edge Intelligence for Beyond 5G Networks

(University of Michigan at Ann Arbor)


- 5G Edge intelligence

 5G Edge Intelligence is a new concept that uses mobile edge computing and edge caching capabilities to provide AI to end users. Edge AI provides real-time intelligence, which enables immediate decision-making. It also allows edge devices to autonomously process and analyze data. 

Edge computing, when combined with 5G, can: 

  • Enhance digital experiences
  • Improve performance
  • Support data security
  • Enable continuous operations in every industry
  • Render 3D images for AR/VR applications
  • Ensure that applications are comfortable for the end-user


5G Edge is important for the deployment of large-scale IoT applications and services. It also supports emerging use cases that are grounded in next-generation technologies like AI, augmented reality (AR), and virtual reality (VR). 


- Edge Intelligence for Beyond 5G Networks

Beyond fifth-generation (B5G) networks, or so-called “6G”, is the next-generation wireless communications systems that will radically change how Society evolves. 

Edge intelligence is emerging as a new concept and has extremely high potential in addressing the new challenges in B5G networks by providing mobile edge computing and edge caching capabilities together with AI to the proximity of end users.

In edge intelligence empowered B5G networks, edge resources are managed by AI systems for offering powerful computational processing and massive data acquisition locally at edge networks. 

AI helps to obtain efficient resource scheduling strategies in a complex environment with heterogeneous resources and a massive number of devices, while meeting the ultra-low latency and ultra-high reliability requirements of novel applications, e.g., self-driving cars, remote operation, intelligent transport systems, Industry 4.0, smart energy, e-health, and AR/ VR services.

By integrating AI functions into edge networks, radio networks become service-aware and resource-aware to have a full insight into the operating environment and can adapt resource allocation/orchestration in a dynamic manner. 

Despite the potential of edge intelligence, however, many challenges also need to be addressed in this new paradigm. Until now, limited research efforts have been made on edge intelligence for B5G networks.  


[More to come ...]

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