How Will 5G and Future 6G Keep Our Movements Seamless?

5G networks and the upcoming 6G promise lightning‑fast speeds, near‑zero latency, and massive connection capacity. Yet a key hurdle lies in keeping our smartphones, tablets, and wearables connected while they switch from one cell tower to another (handover), even during 4K video streaming or online gaming. In practice, as you move across coverage zones, your device must "jump" to a new tower in a split second. With high‑definition content and augmented‑reality apps, data traffic has exploded, making it harder to maintain high quality of service (QoS). Researchers are embedding artificial intelligence and machine learning into network systems: algorithms that predict user paths, optimise handover timing, and cut energy use. This not only boosts user experience but also supports sustainable development goals by reducing the environmental footprint of infrastructure. Future networks will need to be even more flexible, reliable, and scalable to power autonomous vehicles, smart cities, and countless connected devices.

Handover (HO) in 5G/6G architectures relies on control protocols such as Xn‑AP and NG‑AP, which manage signaling between gNodeBs (gNB) and the core network. Complexity rises with Massive MIMO, which uses hundreds of antennas to form directional beams (beamforming). Precise synchronization of phase and amplitude parameters is required; otherwise, signal quality can degrade during cell transitions. Moreover, 5G introduces the concept of "network slicing"—virtual partitions dedicated to specific services (e.g., e‑health, gaming). Each slice has distinct KPIs (latency, throughput, reliability) that must be upheld during HO. To optimise these processes, machine learning (ML) algorithms employ predictive models based on location, speed, and network load data. Techniques like reinforcement learning (RL) enable the system to learn dynamic handover policies, minimizing handover delay and packet loss. From an energy perspective, "green handover" solutions use adaptive transmission power control and temporary deactivation of unnecessary antennas (cell sleeping). These strategies lower energy consumption per transmitted bit, supporting sustainability goals. Finally, 3GPP standardisation (Release 18 and beyond) foresees AI‑native functions within the Service Based Architecture (SBA), allowing end‑to‑end orchestration of mobility processes, with continuous KPI monitoring and real‑time feedback to improve reliability, scalability, and energy efficiency of future 6G networks.