MIMO Mode Switching Using Performance Indicators for BLER Recovery
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Solution Overview
Problem
Existing wireless communication systems face challenges in efficiently adapting transmission modes to maintain optimal packet transmission performance due to varying network conditions and user equipment demands.
Innovation Solution
A base station processor dynamically switches between transmit antenna selection and precoding matrix indicator modes based on performance indicators, such as throughput and block error rate, to adapt transmission modes and recover from performance degradation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the base station frequently switches between transmission modes to adapt to varying network conditions, then the adaptability and responsiveness to performance degradation improve, but the system stability and reliability deteriorate due to excessive switching
Solution Approach 1:
The system dynamically adjusts transmission modes based on real-time performance indicators. The base station monitors packet transmission performance and switches between transmission modes (e.g., MIMO modes) adaptively rather than using fixed or overly frequent switching, resolving the contradiction between adaptability and stability
Solution Approach 2:
The system implements feedback mechanisms by monitoring performance indicators such as packet transmission success rates and block error rates. Based on this feedback, the base station determines when mode switching is necessary, ensuring switching occurs only when performance degradation is detected, thus maintaining both adaptability and system stability
2Reliability
If the base station implements strict switching prevention mechanisms to maintain system stability, then reliability improves, but the responsiveness to performance degradation and ability to recover from inferior modes deteriorates
Solution Approach 1:
The system performs preliminary assessments by monitoring performance indicators over time periods or packet counts before triggering mode switching. This preliminary action ensures that switching occurs proactively when degradation is detected, maintaining both stability and recovery speed
Solution Approach 2:
The system changes operational parameters (transmission modes) based on monitored performance indicators. By adjusting modes such as MIMO configurations in response to measured performance degradation, the system maintains stability while enabling timely recovery when necessary
3Measurement precision
If the base station monitors performance indicators continuously to detect degradation quickly, then the detection precision and responsiveness improve, but the computational complexity and energy consumption increase
Solution Approach 1:
The system monitors performance indicators for specific periods or packet counts rather than continuously without limit. This partial monitoring approach achieves sufficient detection precision while reducing unnecessary computational complexity and energy consumption from excessive monitoring
Solution Approach 2:
The system replaces complex continuous monitoring mechanisms with simpler threshold-based detection methods. By using predefined thresholds for performance indicators and time/packet counts, the system achieves effective degradation detection with reduced computational complexity
Data Source
AI summary
An embodiment includes performing a fast switching between different multiple-input multiple-output (MIMO) modes, including switching between a transmit antenna selection mode and a precoding matrix indicator mode, based on one or more performance indicators in order to determine whether to overwrite a determined MIMO mode, where the performance indicator can be any combination of performance metrics including one or more of a block error rate (BLER), an average outer-loop rate control (OLRC) value, among others.