Predictive Mobility Management for 5G mmWave Handover Optimization
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Solution Overview
Problem
5G mmWave networks face challenges with frequent mobility management processing due to high vehicular speeds and dense antenna deployments, leading to handover failures, increased control channel load, and device overheating, especially in high-speed environments like highways.
Innovation Solution
Implementing a predictive mobility management mechanism that generates a handover schedule based on device location, speed, and travel direction, allowing for optimized intra- and inter-cell site handovers without requiring user equipment-based measurement control signaling, thereby reducing overhead processing and signaling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If frequent mobility management processing is performed to handle high vehicular speeds and dense antenna deployments, then handover reliability is improved, but control channel load increases and device overheating occurs
Solution Approach 1:
The patent applies preliminary action by pre-calculating and pre-scheduling handover parameters before actual handover events occur. The network calculates optimal handover timing and parameters in advance based on predicted device trajectories and cell coverage areas, storing these pre-computed values for rapid execution during handover, thereby reducing real-time processing burden and control channel load while maintaining handover reliability
Solution Approach 2:
The patent implements feedback mechanisms where the network continuously monitors device location, speed, and handover execution outcomes. This feedback information is used to refine future handover predictions and adjustments, creating a closed-loop system that adapts to actual conditions while reducing overall control channel traffic through more accurate predictive algorithms
2Measurement precision
If user equipment-based measurement control signaling is used for handover, then measurement accuracy is improved, but overhead processing and signaling increase
Solution Approach 1:
The patent introduces network-side intermediaries that perform measurement calculations and handover decisions on behalf of the user equipment. Instead of relying solely on UE-based measurements and reporting, the network uses its own resources to calculate optimal handover parameters based on predicted device trajectories, effectively mediating the measurement and decision-making process to reduce UE processing overhead and signaling burden
Solution Approach 2:
The patent replaces the traditional mechanical measurement and reporting mechanism with a predictive computational model. Rather than having the UE physically measure and report signal characteristics for each potential handover target, the system uses computational predictions of device trajectory and coverage area to determine handover timing, substituting complex real-time measurements with more efficient predictive calculations
Data Source
AI summary
A mobility management optimizing function in a wireless network receives geographic location information associated with a user equipment device (UE), wherein the UE is associated with a vehicle and generates a predictive handover schedule based on the received location information. Handover processing is initiated based on the predictive handover schedule, wherein initiating the handover processing comprises: transmitting one or more handover initiation messages to a plurality of cell sites in a service provider wireless network at times based on the predictive handover schedule, wherein, upon receipt of a handover initiation message, the plurality of cell sites will initiate handover processing based on the received handover initiation message.