AGC-Based Interference Identification in Wireless Receivers
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional filtering methods for mitigating interference in wireless communication systems, such as LTE, are costly and inefficient due to over-dimensioning for worst-case scenarios and inability to anticipate changing interference characteristics, leading to excessive filtering capacity and failure to protect against new interferences.
Innovation Solution
A method that monitors automatic gain control (AGC) events and generates statistics to identify interferences, evaluates performance degradation, and proposes mitigation solutions, including adjusting frequency, IRC, scheduling restrictions, and filter modifications, allowing for simpler filter designs and cost savings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If conventional filtering methods are used to mitigate interference, then interference attenuation is achieved, but system cost increases due to over-dimensioning for worst-case scenarios
Solution Approach 1:
The patent implements dynamic interference mitigation by continuously monitoring AGC events and adapting filter configurations in real-time based on actual interference conditions. Instead of using fixed, over-dimensioned filters designed for worst-case scenarios, the system dynamically adjusts filtering capacity to match current interference levels, thereby reducing cost while maintaining effective interference attenuation.
Solution Approach 2:
The system changes filtering parameters dynamically based on monitored interference characteristics. By analyzing AGC event patterns and interference statistics, the system adjusts filter bandwidth, center frequency, and attenuation levels to match actual interference conditions rather than relying on static worst-case design parameters, reducing unnecessary filtering capacity and associated costs.
2Device complexity
If predetermined filtering levels are used, then design simplicity is maintained, but adaptability to changing interference characteristics is lost
Solution Approach 1:
The patent implements a feedback mechanism that continuously monitors AGC events and interference statistics, then uses this information to automatically adjust filter configurations. The system feeds back actual interference measurements to the filtering subsystem, enabling it to adapt to changing interference characteristics while maintaining a relatively simple overall design architecture.
Solution Approach 2:
The system performs self-configuration by automatically analyzing its own AGC event patterns and interference statistics to determine optimal filter settings. Instead of requiring manual reconfiguration or complex external control systems, the filtering subsystem serves itself by using internally generated statistics to adapt its own parameters, balancing simplicity with adaptability.
3Reliability
If filtering capacity is increased to handle all possible interference scenarios, then reliability improves, but device complexity and cost increase
Solution Approach 1:
The system performs preliminary analysis of interference patterns by monitoring AGC events and building statistics before configuring the filtering subsystem. By proactively identifying interference characteristics and predicting potential issues, the system can pre-configure appropriate filter parameters, ensuring reliable protection without needing excessive filtering capacity for all possible scenarios.
Solution Approach 2:
The patent implements dynamic filtering capacity adjustment that scales the filtering subsystem's capability to match actual interference conditions. When interference levels are low, the system reduces filtering capacity to avoid unnecessary complexity; when interference increases, the system automatically expands filtering capacity to maintain reliable protection, thereby optimizing the reliability-complexity tradeoff.
4Measurement precision
If AGC monitoring and statistics generation are implemented, then interference identification accuracy improves, but processing complexity increases
Solution Approach 1:
The system uses its existing AGC subsystem to generate interference statistics without requiring separate dedicated measurement hardware or complex external monitoring equipment. By repurposing the AGC event data already being collected for gain control purposes, the system achieves accurate interference identification while minimizing additional processing complexity.
Solution Approach 2:
The AGC monitoring mechanism serves multiple functions simultaneously: it performs its primary gain control function while also generating interference statistics for identification and mitigation purposes. This multi-functionality allows the system to achieve accurate interference measurement without adding separate dedicated measurement systems, thereby improving identification accuracy without proportionally increasing processing complexity.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Interference in a wireless communication system receiver, such as at a base station (200, 1400), is identified based on monitoring automatic gain control (AGC) events. AGC statistics in combination with base band processing are used to identify the interference. Performance degradation is evaluated, and interference mitigation solutions are proposed based on the identified interference. Mitigation solutions include IRC, scheduling restrictions, and filter modifications including replacement of filters.