An Adaptive Threshold Tracking Area Update and Selective Probabilistic Paging Scheme for Signaling Cost Reduction in 5G NR Networks

Abstract

Tracking area update (TAU) and paging are two competing signaling-cost characteristics of 5G NR networks: a smaller registration area reduces paging cost but increases TAU signaling and vice versa. The majority of existing schemes optimize one parameter while fixing the other and apply a single network-wide parameterization to all users regardless of their heterogeneous call and mobility patterns. This paper proposes ATAU-SP, a scheme that manages both operations jointly, on a per user equipment (UE) basis: each UE maintains an online estimate of its call-to-mobility ratio (CMR) and triggers a TAU only after an adaptive movement threshold derived by minimizing a per UE cost function, with a dwell-time guard that suppresses boundary ping-pong updates. The network builds a residence-probability distribution from a learned Markov mobility model and pages cells in descending probability rounds up to a delay bound. We derive a closed-form analytical cost model and validate it as a provable upper bound against a custom discrete-event simulator. The results show that a well-tuned TAL scheme is the lowest-cost baseline over most of the moderate CMRs, ATAU-SP-ML attains the lowest cost at high CMR, and plain ATAU-SP is best only at very low CMR. Nonetheless, ATAU-SP variants dominate the classical static, distance-, movement-, and time-based schemes throughout, and both ATAU-SP and TAL require materially less machinery per UE state and network side than a full TAL list distribution subsystem.