Network Access Center of Gravity for Dynamic Antenna Lobe Adjustment
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Solution Overview
Problem
Existing telecommunications networks fail to dynamically adjust network access and communication services based on the location and mobility of user equipment (UE), leading to inconsistent signal quality and underutilization of network assets.
Innovation Solution
A system and method that dynamically adjusts the center of gravity for network access and communication (CoGNAC) by using a center of gravity engine to analyze trace events and geo-location measurements of UEs, determining a CoGNAC value, and instructing operations support systems to adjust antenna lobes to optimize service for high-value or mobility-sensitive UEs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the network uses fixed antenna configurations to provide coverage, then network infrastructure complexity is reduced, but signal quality consistency for mobile UEs deteriorates
Solution Approach 1:
The patent implements dynamic antenna beamforming that continuously adjusts radiation patterns based on real-time UE location and mobility data. The system transitions from fixed static configurations to adaptive dynamic configurations, where antenna elements are electronically steered to track moving UEs, thereby maintaining consistent signal quality without adding physical infrastructure complexity
Solution Approach 2:
The system changes operational parameters of antenna elements including phase, amplitude, and beam direction dynamically based on UE characteristics. By modifying these electrical parameters rather than physical structures, the network maintains signal consistency for mobile devices while keeping infrastructure simple and fixed
2Reliability
If the network dynamically adjusts antenna beams to track individual UEs, then signal quality for mobile UEs is improved, but network control system complexity increases
Solution Approach 1:
The patent implements self-organizing network capabilities where the system automatically tracks and adjusts antenna beams based on UE mobility patterns without requiring manual intervention. The network uses algorithms that autonomously process UE location data and reconfigure antenna patterns, reducing the need for complex centralized control while maintaining signal quality
Solution Approach 2:
The system continuously receives feedback from UE location measurements and signal quality metrics, then automatically adjusts antenna beam directions in response. This closed-loop feedback mechanism enables dynamic tracking of mobile UEs while using standardized protocols to manage control complexity
3Ease of operation
If the network provides uniform service coverage to all UEs, then network operation simplicity is maintained, but service quality for high-value UEs deteriorates
Solution Approach 1:
The patent applies different service quality levels to different UE groups based on their value and requirements. High-value UEs receive enhanced service with dedicated beamforming and priority resource allocation, while standard UEs receive basic coverage. This localized quality differentiation improves service for important customers without significantly complicating overall network operation
Solution Approach 2:
The system applies enhanced beamforming and tracking resources selectively to high-value UEs rather than uniformly to all devices. By concentrating advanced capabilities on a subset of important customers, the network improves their service quality while maintaining simpler operation for the broader user base
4Device complexity
If the network uses static resource allocation, then network management complexity is reduced, but network asset utilization deteriorates
Solution Approach 1:
The patent implements dynamic resource allocation that adjusts network asset distribution based on real-time UE location, mobility patterns, and service requirements. Antenna beams and radio resources are dynamically reassigned to follow moving UEs and prioritize high-value connections, significantly improving network asset utilization without requiring complex manual management
Solution Approach 2:
The system periodically reevaluates UE positions and reallocates network resources in scheduled intervals. This periodic dynamic adjustment allows the network to adapt to changing conditions and improve asset utilization through automated, time-based resource redistribution rather than static allocation
Data Source
AI summary
Systems, methods, and computer-readable media are provided for dynamically adjusting a center of gravity for network access and communication service. Information comprising trace events and geo-location measurements of one or more UEs is initially received. Next, a network configuration corresponding to a node and profile information corresponding to the one or more UEs is retrieved. The profile information is utilized to determine a CoGNAC value for each of the one or more UEs. Based on the information and the CoGNAC value for each of the one or more UEs, a center of gravity is forecast for at least a portion of the node. Based on the forecasted center of gravity, operations support systems at a core network are engaged to provide instructions to the node to automatically make an angular adjustment for a lobe provided by at least the portion of the node.