Radio Link Error Rate Prediction Using Conditional Codeword Probabilities
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Solution Overview
Problem
Existing methods fail to accurately predict the block error rate of a codeword (CW2) when its decoding is dependent on the correct decoding of another codeword (CW1), due to differences in code-rates, block-sizes, and operating SINR-point, among other factors.
Innovation Solution
Estimating the block error rate of CW2 by using channel state information and conditional error probabilities, specifically through modified methods like Effective Exponential Sum of SINR Mapping (EESM), Mean Mutual Information per Bit (MMIB), and SINR moments, which account for the interdependencies between CW1 and CW2, and extending these methods to multiple codewords.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional error rate estimation methods are used for CW2, then the estimation process is simple, but the prediction accuracy is poor due to ignoring interdependencies with CW1
Solution Approach 1:
The patent introduces an intermediary conditional error probability P(CW1 error|CW2 decoded) that mediates between the channel state information and the final error rate estimation. This conditional probability acts as a bridge that captures the interdependency between CW1 and CW2 decoding, allowing accurate error rate prediction without requiring complex joint decoding analysis.
Solution Approach 2:
The patent segments the error rate estimation process into distinct components: channel state information estimation, conditional error probability calculation, and final error rate computation. This segmentation allows each component to be optimized independently while maintaining overall accuracy, resolving the contradiction between simplicity and precision.
2Measurement precision
If conditional error probabilities and interdependencies are considered, then prediction accuracy improves, but computational complexity increases
Solution Approach 1:
The patent changes the parameter representation from requiring full joint probability distributions to using specific conditional error probabilities and moment-based statistics. This parameter transformation reduces computational complexity while maintaining estimation accuracy, as the conditional probabilities can be derived from existing channel state information without exhaustive computations.
Solution Approach 2:
The patent uses moment-based statistics (mean, variance, higher-order moments) as simplified copies of the full channel state distribution. These statistical moments capture the essential characteristics needed for accurate error rate prediction without requiring complete knowledge of the joint distribution, thereby reducing computational power requirements.
3Adaptability or versatility
If multiple codewords with different code-rates and block-sizes are handled, then system adaptability improves, but estimation accuracy deteriorates due to varying operating conditions
Solution Approach 1:
The patent develops a universal estimation framework that handles multiple codewords with different code-rates, block-sizes, and modulation schemes through a common mathematical formulation. The conditional error probability approach and moment-based statistics provide a unified methodology that adapts to various codeword configurations without sacrificing accuracy, enabling multi-functionality while maintaining precision.
Data Source
AI summary
A method for predicting performance of a radio link in a wireless communication terminal including hypothesizing a second codeword including information associated with a hypothesized first codeword, obtaining channel state information from a received signal, and estimating a decoder error rate of the first codeword under a condition that the second codeword may not be decoded correctly, wherein the decoder error rate is estimated using the channel state information.