On the Performance of Location Management in 5G Network Using RRC Inactive State

• Published in: IEEE access Vol. 10; pp. 65520 - 65532
• Main Authors: Oliveira, Lidiano A. N., Alencar, Marcelo S., Lopes, Waslon T. A., Madeiro, Francisco
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 3GPP; 5G mobile communication; 5G networks; Cellular mobile system; Costs; Densification; Genetic algorithms; location management; location update; Long Term Evolution; Network latency; Optimization; Paging; Radio access networks; RNA; RRC states; Signaling; Wireless networks
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2022.3178383

Among the characteristics in fifth generation (5G) networks, a massive number of devices and a network densification stand out. Hence, efficient location management is a key factor in enabling the network to track each user under the coverage area. In order to fulfill the requirements of 5G, a novel location management strategy was introduced by the 3rd Generation Partnership Project (3GPP) based on a new Radio Resource Control (RRC) state. This article presents a new methodology to find out an optimum network configuration that minimizes the signaling costs associated with the location management scheme for 5G networks. In addition to procedures triggered by the core network, the signaling costs are calculated taking into account the paging and update procedures performed in the Radio Access Network (RAN). A genetic algorithm is applied to optimize the network by reducing signaling costs caused by location management procedures, obtained from a 5G network system-level simulator focusing on mobility events. The proposed approach is compared to the schemes used in previous mobile networks. The results indicate that the new scheme decreases the signaling cost and reduces latency in various network sizes and user profile.