Channel Encoding with Data Compression for Lower BLER
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing communication systems face high block error rates (BLER) due to limited error protection capability of channel encoding, leading to excessive resource consumption and delays from retransmissions.
Innovation Solution
The method involves compressing and aligning to-be-transmitted data with alignment bits to reduce the code rate during channel encoding, enhancing error protection capability and improving transmission reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If channel encoding is performed on original data without compression, then the encoding process is simple, but the code rate is high and error protection capability is limited
Solution Approach 1:
Data compression is performed before channel encoding to reduce the data length. This preliminary action allows the subsequent encoding process to achieve better error protection with the same resources, or equivalently, improves error protection capability without proportionally increasing complexity
Solution Approach 2:
The code rate is adjusted by changing the input data length through compression. By reducing the data length before encoding, the effective code rate decreases, improving error protection capability while maintaining a manageable encoding complexity
2Reliability
If the code rate is reduced to improve error protection, then transmission reliability improves, but the data processing complexity increases
Solution Approach 1:
Data compression is performed in advance before encoding, so that when encoding occurs, the data is already in a compressed form. This preliminary compression enables lower effective code rates and better reliability without requiring excessively complex real-time processing during the encoding phase
Solution Approach 2:
The processing is divided into distinct stages: compression stage and encoding stage. This segmentation allows each stage to be optimized independently, with compression handling data reduction and encoding handling error protection, thereby managing overall system complexity
3Reliability
If data is compressed before channel encoding, then the code rate is reduced and error protection capability is improved, but the processing time and complexity increase
Solution Approach 1:
Compression is performed as a preliminary step before encoding, allowing the system to benefit from lower code rates and improved error protection. The trade-off in processing time is accepted as a one-time cost that enables significantly improved transmission reliability
Solution Approach 2:
The compression and encoding processes are integrated into a continuous data flow pipeline. This ensures that once compression begins, the encoded output flows continuously, minimizing idle time and ensuring that the processing time overhead is efficiently utilized
Data Source
AI summary
This application discloses a communication method that comprises obtaining first data, where the length of the first data is A; compressing the first data into second data, where the length of the second data is C; and generating third data based on the second data, where the third data includes the second data and (T−C+p) alignment bits. T is a threshold in the J thresholds that is greater than or equal to C and the closest to C. The J thresholds correspond to A and are greater than 0, with J being a positive integer greater than or equal to 2. p is a quantity of auxiliary check bits and is an integer greater than or equal to 0. The communication method further comprises performing channel encoding on the third data to obtain fourth data and sending the fourth data.