Polar Code Construction for Multi-Rate Blocks With Reduced Memory
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Solution Overview
Problem
Existing wireless communication networks face challenges in efficiently constructing polar codes, particularly in supporting different block sizes and rates, which requires large memory storage for sorting indices and can be inefficient.
Innovation Solution
The method involves dynamically generating sorting indices on the fly using density evolution or Gaussian approximation, rather than storing pre-defined vectors in memory, to construct polar codes efficiently for both traffic and control channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pre-defined sorting index vectors are stored in memory for constructing polar codes, then code construction accuracy is improved, but memory requirements increase significantly
Solution Approach 1:
The patent pre-calculates and stores only the essential sorting index information in lookup tables during system initialization, rather than storing complete sorting index vectors. This preliminary action reduces the memory footprint while maintaining the ability to reconstruct polar codes accurately when needed.
Solution Approach 2:
The patent extracts and stores only the critical sorting index data required for polar code construction in lookup tables, separating this essential information from other data. This extraction approach minimizes memory usage by storing only what is absolutely necessary for accurate code construction.
2Quantity of substance
If dynamic generation of sorting indices is implemented, then memory requirements are reduced, but computational complexity increases
Solution Approach 1:
The patent pre-calculates sorting indices and stores them in compact lookup tables during system initialization. This preliminary computation shifts the computational burden to the initialization phase, allowing the runtime operation to simply retrieve pre-computed values, thereby reducing both memory requirements and runtime computational complexity.
Solution Approach 2:
The patent uses lookup tables that store pre-computed sorting index patterns which can be reused across multiple polar code constructions. Instead of dynamically generating sorting indices each time, the system copies and applies these pre-stored patterns, significantly reducing computational complexity while maintaining accuracy.
3Adaptability or versatility
If polar codes are constructed to support multiple block sizes and rates, then adaptability is improved, but the complexity of managing sorting indices increases
Solution Approach 1:
The patent designs lookup tables with a universal structure that can serve multiple block sizes and code rates. The same lookup table infrastructure supports different polar code configurations, eliminating the need for separate sorting index management for each block size or rate, thereby reducing overall system complexity.
Solution Approach 2:
The patent enables adaptation to different block sizes and rates by changing parameters within the existing lookup table framework. Rather than managing complex sorting indices for each configuration, the system adjusts parameters like block size and rate while reusing the same underlying lookup table structure, simplifying management.
Data Source
AI summary
Methods and apparatus for constructing polar codes are provided. A transmitter determines at least one set of parameters corresponding to data to be transmitted, and a set of sorting indices corresponding to bits of the data to be transmitted based on the set of parameters, the set of sorting indices indicating a position set of the bits to be transmitted. The transmitter polar encodes the data based at least on the set of parameters and the set of sorting indices to generate a coded block of the data, and transmits the coded block of the data.