Multi-Panel UE Panel Prioritization for 5G Energy Saving
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Solution Overview
Problem
Existing 5G network energy saving strategies fail to adequately address the impact on served and potentially served User Equipments (UEs), particularly during handover processes, leading to potential network performance deterioration and increased energy consumption.
Innovation Solution
A method and apparatus for determining a panel prioritization strategy in multi-panel user equipment (MPUE) based on predicted transmissions of reference signals, allowing for dynamic adjustment of panel activation rates to align with network energy saving strategies and minimize unnecessary power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If radio cells are switched off to save energy, then energy consumption is reduced, but network performance deteriorates due to additional traffic on remaining active cells
Solution Approach 1:
The system performs preliminary actions by proactively managing panel activation states before handover occurs. The UE predicts upcoming handovers and pre-activates relevant panels to ensure continuous reference signal reception, avoiding the need for reactive panel activation that would increase energy consumption.
Solution Approach 2:
The system dynamically adjusts panel activation strategies based on predicted handover events. Instead of static panel management, the UE continuously monitors handover predictions and dynamically activates/deactivates panels to match actual network conditions, optimizing the balance between energy saving and performance.
2Measurement precision
If panels are activated frequently to maintain network performance, then measurement accuracy is improved, but power consumption increases
Solution Approach 1:
The system performs preliminary panel activation based on predicted handovers. By knowing in advance when handovers will occur, the UE can pre-activate the necessary panels to ensure reference signal reception is available when needed, rather than continuously activating all panels which would waste energy.
Solution Approach 2:
The system uses feedback from handover predictions to adjust panel activation. The UE receives information about predicted handovers and uses this feedback to intelligently control panel states, activating only when and where needed based on the predicted network conditions.
3Loss of energy
If energy saving strategies are implemented without considering UE impact, then network energy efficiency is improved, but UE service quality deteriorates during handover
Solution Approach 1:
The system applies local quality by treating different panels differently based on their specific roles and predictions. Not all panels are managed uniformly - the system identifies which panels are critical for upcoming handovers and applies different activation strategies to those panels versus others, optimizing both energy saving and UE service quality.
Solution Approach 2:
The system uses handover prediction information as an intermediary that mediates between network energy saving goals and UE service requirements. This intermediary data allows the UE to reconcile conflicting objectives by using prediction knowledge to time panel activation appropriately.
Data Source
AI summary
A method including: receiving, by a multi-panel user equipment from a serving network entity, information indicative of predicted transmissions of reference signals by a serving network entity or target network entity; and applying a panel prioritization strategy for the multi-panel user equipment based on the received information indicative of predicted transmissions of reference signals.