Cellular Network Element State Diagnosis via RF Signal Analysis
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Solution Overview
Problem
The identification and classification of causes of uplink interference in cellular networks is a tedious and inefficient process, often requiring manual input and physical visits to individual cell sites, leading to ineffective remediation of interference issues.
Innovation Solution
A system and method that utilize a network diagnostic platform to analyze radio frequency signal strength data from multiple antennas to determine the state of network elements, identify external interference, and diagnose hardware and interference issues, including incorrect parameter settings and passive intermodulation, enabling automated diagnosis and reporting of interference sources and their impact on network performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual input and physical visits to individual cell sites are used to identify uplink interference causes, then diagnostic accuracy can be achieved, but the process becomes extensive and tedious with high time consumption
Solution Approach 1:
The patent replaces manual mechanical processes (physical visits to cell sites) with an automated electronic system that collects and analyzes RF measurement data from multiple antennas to diagnose uplink interference causes, thereby reducing time consumption while maintaining diagnostic accuracy
Solution Approach 2:
The patent creates a virtual model of the cellular network by collecting RF measurement data from multiple antennas and processing this data through algorithms to identify interference sources, eliminating the need for physical inspection while preserving diagnostic capabilities
2Productivity
If automated diagnostic systems are implemented to reduce manual visits, then time efficiency improves, but system complexity increases
Solution Approach 1:
The patent implements a multi-functional diagnostic system that can identify multiple types of uplink interference sources (external interference, passive intermodulation, hardware issues, parameter settings) through a single unified platform, improving productivity without proportionally increasing complexity
Solution Approach 2:
The system performs self-diagnosis by automatically collecting RF measurement data, processing it through analysis algorithms, and generating diagnostic reports without requiring manual intervention, thereby improving efficiency while keeping the system architecture manageable
Data Source
AI summary
Techniques for monitoring and diagnosing states of wireless network elements having a known impact on uplink interference are presented. In an aspect, a method includes receiving, by a system including a processor, diagnostic data for a cellular network including strength data representative of strengths of radio frequency signals, prior to demodulation, respectively received at a plurality of antennas of a base station of the cellular network over a defined duration of time and at a defined sampling rate. The method further includes, based on analyzing the strength data by the system, determining by the system, a state of a network element of the cellular network.