Receiver BEP Estimation Using Header Re-Decoding in EDGE
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Solution Overview
Problem
Existing bit error probability (BEP) estimation methods in EDGE systems are inaccurate due to the inability to correctly decode header and data parts with errors, leading to degraded estimation accuracy and failure to meet high accuracy requirements.
Innovation Solution
A BEP estimation method that de-shapes and de-punctures coded blocks to obtain channel hard outputs, decodes and analyzes header parts for errors, selects either the header or whole block for re-encoding, and compares re-encoded decisions with channel or header outputs to calculate BEP, allowing for accurate estimation even with corrupted data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional BEP estimation methods are used in EDGE systems, then the estimation process is simple, but the estimation accuracy is degraded and cannot meet high accuracy requirements
Solution Approach 1:
The coded block is segmented into header part and data part, which are processed separately through de-puncturing and decoding. This segmentation allows for more precise error analysis and BEP estimation by treating different parts with appropriate methods, thereby improving measurement precision without excessive complexity increase.
Solution Approach 2:
A re-encoding process is introduced as an intermediary step where the decoded header and data parts are re-encoded to generate re-encoded sequences. These re-encoded sequences serve as intermediaries for comparison with the original channel hard outputs, enabling accurate BEP calculation while maintaining a structured processing framework.
2Reliability
If coded blocks with errors are directly decoded using conventional methods, then the decoding process is straightforward, but the ability to correctly decode header and data parts with errors is lost
Solution Approach 1:
De-puncturing is performed as a preliminary action before decoding, where punctured bits are restored to their original positions in the coded block. This preliminary restoration enables the subsequent decoding process to work with a complete structure, improving reliability by ensuring that error correction can be applied to the full sequence including header and data parts.
Solution Approach 2:
The decoded header and data parts are fed back through a re-encoding process to generate re-encoded sequences. These re-encoded sequences are then compared with the original channel hard outputs to calculate BEP. This feedback mechanism ensures that decoding reliability is maintained by verifying results against the original input and providing accurate error probability measurements.
Data Source
AI summary
A bit error probability (BEP) estimation method includes de-shaping a coded block to obtain a channel hard output block comprising a header hard output and at least one data hard output, de-puncturing and decoding the header hard output to obtain a decoded header part, determining whether the decoded header part has errors, selecting the decoded header part or a decoded whole block as a selected part based on the determination result, wherein the decoded whole block comprises the decoded header part and a decoded data part obtained by de-puncturing and decoding the data hard output, re-encoding the selected part to obtain a re-encoded decision, and comparing the re-encoded decision to the header hard output or the channel hard output corresponding to the selected part to obtain the BEP of the coded block. A receiver employing the BEP estimation method is also provided in the invention.