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, leading to degradeuser Quality of Service (QoS). This paper proposes a velocity-aware adaptive handover control approach for efficient mobility management in 5G ultra-dense networks. The proposed approach dynamically adjusts Handover Control Parameters (HCPs) called Time-to-Trigger (TTT) and Handover Margin (HOM) on the real-time velocity of User Equipment (UE) and signal conditions. The system is modeled as a two-tier heterogeneous network consisting of a macrocell overlaid with multiple small cells, and performance is evaluated using the Cost 231-Hata propagation model. The findings demonstrate that the proposed algorithm significantly reduces the total number of handovers, mitigates the ping-pong effect, and lowers handover failure rates compared to conventional static schemes. The results confirm that velocity-aware adaptive control enhances network reliability, reduces signaling overhead, and improves overall mobility performance in 5G ultra-dense environments.
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
Rogue Base Stations (RBS) remain a persistent security threat to fifth-generation (5G) and emerging sixth-generation (6G) cellular systems by impersonating legitimate infrastructure and exploiting vulnerabilities in pre-authentication signaling and mobility procedures. The risk is particularly critical in vehicular and Vehicle-to-Everything (V2X) environments, where high mobility and millisecond-scale handover operations tightly couple communication reliability with safety-critical control functions. Although prior surveys examine LTE identity catchers and general cellular security threats, they rarely evaluate RBS detection under vehicular mobility dynamics or within the latency and reliability constraints of Ultra-Reliable Low-Latency Communication (URLLC) services. In addition, the limited availability of realistic measurement report (MR) datasets have hindered reproducible benchmarking of data-driven detection methods. This article presents 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 general cellular security. We introduce a method-centric taxonomy that organizes existing approaches into five families based on their primary evidence sources and inference mechanisms: signal anomaly detection, protocol and traffic analytics, RF fingerprinting, network-level frameworks, and machine-learning-based detection. Using a PRISMA-compatible structured literature review across 102 included studies and a structured comparative evaluation framework, each family is analyzed across detection latency, computational overhead, robustness to mobility, false alarm susceptibility, and feasibility within quantified pre-handover decision windows. Direct cross-study quantitative comparison is precluded by heterogeneous reporting conventions across the surveyed literature; the framework, therefore, provides structured qualitative synthesis and indicative performance ranges rather than pooled empirical estimates. The analysis reveals that no individual technique satisfies vehicular URLLC constraints in isolation, motivating layered architectures combining lightweight UE-side detection with edge-assisted and operator-level analytics. A scenario-driven safety analysis links detection error rates to operational consequences across five V2X use cases under varying URLLC severity levels. The survey formalizes evaluation criteria for MR-driven detection and highlights realistic MR generation as a foundation for reproducible evaluation and cross-study comparison in next-generation vehicular communication systems.
Roland Lamptey, M. Saedi, V. Stankovic et al.· IEEE Open Journal of the Com...· 0 citations
In 5G networks, handover management is critical for ensuring seamless mobility, low latency, and high-quality user experiences. However, traditional handover mechanisms suffer from frequent handover failures and ping-pong effects, especially when users move at high speeds or across densely deployed small cells. This paper proposes a mobility-predictionbased handover approach with an adaptive Time-To-Trigger (TTT) mechanism that adjusts dynamically to user speed and mobility patterns. The system comprises three key components: a Mobility Prediction Module utilizing recurrent neural networks (RNNs) to analyze historical movement data and real-time parameters including signal strength and user speed; Dynamic TTT Adaptation that reduces TTT for high-speed users to enable faster handovers while increasing TTT for slow-moving users to prevent ping-pong effects; and a Handover DecisionAlgorithm that integrates predicted mobility with real-time signal quality measurements. Simulation results demonstrate that the approach improves handover success rates, reduces ping-pong effects and enhances overall network performance. Additionally, the adaptive framework contributes to better resource utilization and overall network efficiency, The proposed system achieved 94.2% success rate, 67% fewer ping-pong events, 42ms average delay, 15.8% throughput gain, and 89.4% prediction accuracy with low computational cost.
Sangeetha Saman, M. B., J. D et al.· International Journal of Ele...· 0 citations
Rural highways, agricultural regions, and other infrastructure-limited environments often lack continuous cellular coverage and dedicated vehicular roadside units. Connected vehicles traversing these corridors nevertheless require intermittent links for cooperative awareness messaging, status updates, and low-rate telemetry. IEEE 802.11ah (Wi-Fi HaLow) offers extended sub-GHz reach and low-power operation suited to rapidly deployable, solar- or battery-powered access points where conventional vehicular infrastructure is absent. Selecting a fixed channel bandwidth nonetheless remains difficult: wide channels raise throughput under favourable conditions but erode robustness as distance and mobility increase, whereas narrow channels preserve link margin at the cost of capacity. This paper proposes a signal-to-interference-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. Performance is evaluated through cross-layer analytical modelling and packet-level ns-3 simulation against fixed-width baselines. Results show that no single bandwidth dominates across the mobility–distance envelope: wider channels favour short range and low speed, whereas narrower channels sustain more reliable delivery as conditions deteriorate. Relative to any fixed configuration, adaptive MHz selection yields a more balanced reliability–throughput trade-off for low-rate fallback connectivity along heterogeneous rural routes.
Francis Kagai, Mohsin Murtaza, Kithmini Godewatte Arachchige et al.· IEEE Access· 0 citations
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