Mobility History Information

Description

Mobility History Information (MHI) is a structured data set generated and maintained by the User Equipment (UE) and/or the network, detailing the UE's historical mobility behavior. This information is primarily defined within the context of the Radio Resource Control (RRC) protocol in 5G New Radio (NR). The UE typically logs key mobility events, such as successful handovers, connection re-establishments, and cell reselections, along with associated parameters like the identities of source and target cells, timestamps, and radio conditions at the time of the event. This log forms the MHI record.

The network, specifically the Next Generation NodeB (gNB), can request this information from the UE via RRC signaling, such as during a UE Information Request procedure. Upon receiving the request, the UE provides the MHI report. The gNB's Radio Resource Management (RRM) functions then process this historical data. By analyzing patterns—such as frequent handovers between specific cells, typical movement trajectories, or failure-prone areas—the RRM algorithms can build a predictive model of the UE's mobility.

This predictive capability is central to MHI's operation. For instance, if a UE's history shows it consistently moves from Cell A to Cell B after a short dwell time in Cell A, the serving gNB can proactively prepare resources in Cell B or even initiate a conditional handover earlier and more reliably. This reduces handover failure rates and interruption time. Furthermore, MHI aids in network-centric optimizations. Network Management Systems (NMS) or the gNB itself can aggregate MHI reports from multiple UEs to identify systemic issues like cell coverage holes, persistent interference zones, or unbalanced traffic loads between neighboring cells, guiding corrective configuration changes.

The specifications governing MHI, such as 3GPP TS 38.306 (UE radio access capabilities) and the 28.622/32.42x series (management), define the information elements, reporting procedures, and management aspects. MHI enhances traditional, instantaneous-measurement-based mobility management by adding a temporal dimension, allowing the network to make decisions based on learned behavior rather than just a snapshot of current radio conditions.

Purpose & Motivation

MHI was introduced to address the challenges of mobility management in increasingly dense and heterogeneous 5G and beyond networks. Traditional handover decisions rely heavily on real-time measurement reports (e.g., Reference Signal Received Power - RSRP). While effective, this reactive approach can struggle with high-speed scenarios, ultra-dense deployments, and complex multi-beam environments, leading to late, failed, or unnecessary handovers (ping-pong effects). These failures degrade user experience and consume unnecessary signaling resources.

The core problem MHI solves is the lack of context in mobility decisions. By providing a history of the UE's movements, the network gains predictive insight. This allows for more proactive and intelligent resource management. For example, it enables predictive handovers where the target cell is prepared in advance based on the UE's trajectory, significantly reducing the risk of handover failure and data interruption. This is critical for supporting seamless mobility for use cases like vehicular communications (V2X) and high-speed trains.

Furthermore, MHI supports advanced network automation and Self-Organizing Network (SON) functions. By collecting mobility histories from a population of UEs, operators can perform data-driven optimization of cell boundaries (mobility robustness optimization), antenna tilts, and handover parameters. This moves network tuning from a reactive, manual process to a proactive, data-centric one, improving overall network efficiency and stability. Its specification across both radio access (38-series) and management (28/32-series) standards underscores its role as a key enabler for intelligent, automated 5G systems.

Key Features

• Records historical UE mobility events (handovers, reselections)
• Reportable by UE to gNB via RRC signaling upon network request
• Enables predictive mobility and handover management
• Supports mobility robustness optimization (MRO) and load balancing
• Provides input for network analytics and SON functions
• Defined for 5G NR with backward-compatible management interfaces

Evolution Across Releases

Defining Specifications