EconPapers    
Economics at your fingertips  
 

An Introduction to AI and Routing Problems in Mobile Telephony

Carlos A. S. Oliveira ()
Additional contact information
Carlos A. S. Oliveira: AT&T Labs Inc.

Chapter Chapter 6 in Handbook of Artificial Intelligence and Data Sciences for Routing Problems, 2025, pp 107-122 from Springer

Abstract: Abstract Routing optimization in mobile telephony aims to enhance network efficiency and service quality by addressing complex and dynamic challenges such as call routing, handover management, load balancing, and energy consumption. Artificial intelligence (AI) and machine learning techniques are key to solving these problems, allowing for real-time, data-driven decisions that optimize resources, reduce latency, and ensure seamless communication. This paper explores various aspects of routing optimization, including cell site placement, radio resource allocation, quality of service (QoS)-based routing, and network security, highlighting AI’s crucial role in modern mobile networks.

Keywords: Optimization; Routing; Telephony; Telecommunications; Interference (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-031-78262-6_6

Ordering information: This item can be ordered from
http://www.springer.com/9783031782626

DOI: 10.1007/978-3-031-78262-6_6

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-04-02
Handle: RePEc:spr:spochp:978-3-031-78262-6_6