Adaptive Beam Load Balancing for Wireless Network QoS
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Solution Overview
Problem
Wireless network providers face challenges in optimizing Quality of Service (QoS) and efficiently utilizing network resources due to uneven distribution of User Equipment (UE) across multiple beams at a base station, leading to potential interference and capacity issues.
Innovation Solution
The implementation of an Adaptive Beam Load Balancing System (BLBS) that dynamically modifies beam configurations based on UE-generated information, such as signal quality metrics and predictive models, to optimize UE connections and balance network load across beams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If beam configurations are statically configured without dynamic adjustment, then device complexity is reduced, but Quality of Service and network resource utilization deteriorate due to uneven UE distribution
Solution Approach 1:
The patent implements dynamic beam configuration adjustment where the network entity continuously monitors UE distribution across beams and modifies beam parameters (such as beam width, direction, or power) in real-time based on current network conditions. This transforms the static beam configuration into a dynamic system that adapts to changing UE distributions, thereby improving QoS without requiring overly complex manual configuration management.
Solution Approach 2:
The system employs feedback mechanisms where the network entity receives information about UE distribution and beam performance metrics, processes this information to determine optimal beam configurations, and applies adjustments accordingly. This closed-loop feedback system enables automatic optimization of beam configurations based on actual network conditions, improving QoS while reducing the need for complex manual intervention.
2Productivity
If beam configurations are dynamically adjusted based on UE information, then network resource utilization and load balancing improve, but device complexity and processing requirements increase
Solution Approach 1:
The network entity pre-establishes beam configurations and monitoring mechanisms that are ready to respond to UE distribution changes. By having predetermined configuration options and automated decision-making frameworks in place beforehand, the system can quickly adapt to changing conditions without requiring complex real-time calculations, thus improving network resource utilization while managing processing complexity.
Solution Approach 2:
The system enables automatic self-optimization where the network entity autonomously monitors UE distribution, determines optimal beam configurations, and applies adjustments without requiring complex external intervention. This self-service capability improves network resource utilization by continuously optimizing beam configurations while reducing the processing burden on external management systems.
3Quantity of substance
If multiple beams are used to provide RF connectivity, then network capacity increases, but interference between beams worsens due to spectral reuse
Solution Approach 1:
The patent applies local quality optimization by adjusting beam parameters (such as beam width, direction, or power levels) specifically for each beam based on local UE distribution and interference conditions. This allows the system to maintain high network capacity through multiple beams while minimizing interference between them by tailoring each beam's characteristics to its specific operational context, thereby resolving the contradiction between capacity and interference.
Data Source
AI summary
A system described herein may provide a technique for adaptive and dynamic beamforming in a radio access network (“RAN”) of a wireless network, based on information received from User Equipment (“UEs”) connected to the RAN, and/or information that can be attributed to UEs and/or users associated with UEs connected to the RAN. For example, a Beam Load Balancing System (“BLBS”) of some embodiments may use such information to identify beams, of one or more base stations, for which a configuration should be modified in order to provide RF connectivity to one or more UEs in a manner that optimizes Quality of Service (“QoS”) provided to the UEs and/or efficiently utilizes network resources.