Beam Scanning Prioritization via Historical Signal Strength Analytics
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Solution Overview
Problem
Current wireless communication networks face inefficiencies in beam management, particularly in prioritizing radio beams for scanning and attachment by user equipment (UE) devices and network devices, leading to suboptimal connection establishment and maintenance.
Innovation Solution
Implementing systems and methods that utilize analytics, such as machine learning algorithms, to generate prioritizations of beams based on historical signal strengths and attachment data, allowing UE and network devices to prioritize beam scanning and attachment operations according to geographic location, time, and environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If beam scanning is performed without prioritization, then all beams are scanned uniformly, but the time and resources required for connection establishment increase
Solution Approach 1:
The system performs preliminary actions by generating prioritization lists of beams in advance based on historical signal strength data, geographic location information, and attachment rates. These pre-computed prioritizations are stored and readily available when connection establishment is needed, eliminating the need for real-time analysis during the scanning process and thus reducing connection establishment time while improving scanning efficiency.
2Measurement precision
If historical data collection is implemented, then beam prioritization accuracy improves, but system complexity increases
Solution Approach 1:
The analytics engine is designed as a multi-functional system that simultaneously performs multiple tasks: collecting historical signal strength data, analyzing geographic location patterns, calculating attachment rates, generating prioritization lists, and updating the prioritization database. This universal approach consolidates what could be separate complex functions into a single integrated system, improving measurement precision without proportionally increasing overall system complexity.
Solution Approach 2:
The system implements self-service mechanisms where the analytics engine automatically collects historical data from network operations, processes this data to generate prioritizations, and updates the prioritization database without requiring manual intervention. The system serves itself by continuously improving its own accuracy through automated data collection and analysis, reducing the operational complexity burden despite the sophisticated analytics performed.
3Productivity
If beam prioritization based on historical data is used, then connection establishment efficiency improves, but data storage requirements increase
Solution Approach 1:
The system extracts and stores only the most essential and relevant features from historical data for prioritization purposes. Instead of storing complete raw historical datasets, the analytics engine extracts key parameters such as average signal strength, geographic location associations, and attachment rate metrics. This extraction approach maintains connection establishment efficiency by preserving the critical information needed for prioritization while significantly reducing the volume of data that must be stored and managed.
Data Source
AI summary
Systems and methods for radio beam management for a wireless network are described. An illustrative system includes a memory configured to store instructions and a processor configured to execute the instructions to determine that a user equipment (UE) device is located at a geographic location, determine a prioritization of beams associated with the geographic location, and direct the UE device to apply the prioritization of beams associated with the geographic location for beam scanning at the geographic location. The prioritization of beams may be generated based on historical beam signal strengths at the geographic location. In certain examples, an analytics engine applies a machine learning algorithm to generate the prioritization of beams based on inputs that include historical beam signal strengths reported by UE devices at the geographic location.