Jul 2026· International Conference on Computer, Information and Telecommunication Systems· pp. 1-8· 0 citations· 19 references
Abstract
Frequent handovers remain a challenge in vehicular fifth-generation (5G) networks, especially in dense urban areas with small cells and intersections. Conventional handover decisions mainly follow the current radio condition and may select a target that is not stable along the vehicle's future route. This paper proposes a mobility- and radio-aware handover control method for 5G vehicular networks. The method keeps the default received-signal trigger as the initial detector, predicts a short future route from lane position, heading continuity, road topology, and transition-support information, and validates the candidate using a historical signal-to-interference-plus-noise ratio (SINR) grid map. It suppresses candidates that indicate a ping-pong return to the serving next-generation NodeB (gNB) or a short stay before another gNB becomes preferable, while a current SINR-based rescue rule avoids keeping the user equipment (UE) on a weak serving link. In a real-map Innsbruck urban microcell scenario with 85 vehicular UEs and 24 gNBs, the proposed method reduces total handovers by 28.9%, ping-pong handovers by 55.9%, and short-stay handovers by 69.0% compared with the default policy. The post-simulation reference signal received power (RSRP) evaluation also remains strong, with 99.46% of the proposed-method samples in the Excellent category and 0.54% in the Good category. These results show that mobility prediction with future SINR-map validation improves vehicular handover stability while preserving serving-link quality.
The deployment of Ultra-Dense Networks (UDNs) in 5G systems is to meet the growing demand for high data rates and massive connectivity. However, the dense deployment of small cells increases handover frequency, leading to challenges such as handover failures (HOF), unnecessary handovers, and the ping-pong effect, leadi...
Halah Hassen Aldumaini, Hanadi Esmeail Yahya, Oloof Ameen Mohmmed et al.· 2026 6th International Confe...· 0 citations
A proactive mitigation framework that applies the unified Autoregressive Recurrent Neural Network (AR-RNN) that significantly improves network reliability, reducing the network outage probability by up to 50% compared to standard reactive handover procedures.
The proposed framework separates network control from forwarding, maintains a global view of vehicular network state, classifies V2X flows by service criticality, and dynamically selects routes and bandwidth allocations using delay, congestion, handover, and priority constraints.
Swadhin Singh, Swatantra Kumar, Mr. Rahul Kumar· International Journal of Adv...· 0 citations
A vehicular-oriented survey of RBS detection in 5G and beyond networks, explicitly addressing mobility-constrained detection, handover-security interactions, and V2X safety requirements that are not systematically addressed in prior surveys, which primarily focus on pre-5G threat models, IMSI-catcher attacks, or genera...
Roland Lamptey, Mohammad Saedi, V. Stankovic et al.· IEEE Open Journal of the Com...· 0 citations
A mobility-predictionbased handover approach with an adaptive Time-To-Trigger (TTT) mechanism that adjusts dynamically to user speed and mobility patterns that improves handover success rates, reduces ping-pong effects and enhances overall network performance is proposed.
Sangeetha Saman, M. B., J. D et al.· International Journal of Ele...· 0 citations
A signal-to-interference-plus-noise ratio-plus-noise ratio (SINR)-adaptive bandwidth selection scheme that dynamically selects among 1, 2, 4, and 8 MHz IEEE 802.11ah channels according to prevailing link quality is proposed.
Francis Kagai, Mohsin Murtaza, Kithmini Godewatte Arachchige et al.· IEEE Access· 0 citations
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