User Level Mobility Load Balancing in Wireless Networks
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Solution Overview
Problem
Current mobility load balancing techniques in wireless networks primarily focus on cell-level optimizations, which can lead to user experience degradation and lack control over individual user equipment (UE) offloading, especially in scenarios involving emergency calls, VoLTE, or fast-moving UEs, as they do not effectively prioritize UE selection or manage offloading to target cells.
Innovation Solution
Implementing a multi-dimensional load balancing algorithm that classifies UEs based on metrics such as GBR, emergency/normal status, speed of movement, and relative neighbor power, allowing for heuristic decision-making to offload UEs to optimize network resource utilization while minimizing user experience degradation by prioritizing active UEs and avoiding repeated selection failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cell-level load balancing is implemented, then network resource utilization is optimized, but user experience degradation occurs and individual UE offloading control is lost
Solution Approach 1:
The patent segments the load balancing control from cell-level to UE-level by introducing a per-UE plane in the control plane. This allows individual UE offloading decisions to be made based on specific UE characteristics (emergency status, GBR, speed), enabling fine-grained control that optimizes both network resource utilization and user experience for each individual UE.
Solution Approach 2:
The patent applies local quality by making load balancing decisions specific to each UE's local characteristics rather than applying uniform cell-level policies. The system evaluates individual UE attributes (emergency call status, GBR requirements, movement speed) to determine optimal offloading, thereby tailoring the quality of service to each user's specific needs while maintaining overall network efficiency.
2Productivity
If cell-level parameters are controlled for load balancing, then resource utilization improves, but control over individual UE offloading is lost
Solution Approach 1:
The control mechanism is segmented into multiple planes including a new per-UE plane that enables individual UE offloading control. This segmentation allows the system to maintain cell-level resource optimization while simultaneously providing fine-grained control over each UE's offloading decisions based on UE-specific characteristics.
Solution Approach 2:
The system dynamically adjusts offloading decisions based on real-time UE characteristics such as emergency status, GBR requirements, and movement speed. This dynamic control mechanism enables flexible UE-level management that adapts to changing user needs and network conditions, improving both ease of operation and resource utilization.
3Measurement precision
If UE-level information is used for load balancing, then offloading accuracy improves, but algorithm complexity increases
Solution Approach 1:
The patent evaluates specific UE-level attributes (emergency status, GBR, speed) to make precise offloading decisions. By focusing on relevant local characteristics rather than processing all possible UE parameters, the system achieves high offloading accuracy while managing algorithmic complexity through targeted evaluation of key UE-specific metrics.
Data Source
AI summary
A method of providing user level mobility load balancing is provided, the method comprising: classifying a group of User Equipments (UEs) in a cell into multidimensional planes based on metrics associated with the UEs; defining thresholds for each dimension; using the defined thresholds determining to discard or select certain planes of a dimension and the UEs contained in the planes; and identifying a best UE of the UEs contained in selected planes for offload.