Binary Polar Code Rate Allocation for Multilevel Modulation
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Solution Overview
Problem
Extending polar codes to systems using higher-order modulation techniques is challenging due to output bits experiencing different effective channels, making standard polar code design techniques not generally applicable.
Innovation Solution
Implementing multilevel coding (MLC) with binary alphabet polar codes, where multiple bits are encoded using different binary polar codes with varying code rates to ensure each bit level experiences the same effective signal-to-noise ratio (SNR), allowing for efficient error rate management across bit levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If standard polar code design techniques are used with higher-order modulation, then the system can achieve capacity of binary-input memoryless symmetric channels, but the output bits experience different effective channels making the design not generally applicable
Solution Approach 1:
The patent segments the coding process into multiple levels, where each bit level is independently coded using binary polar codes. This segmentation allows the system to handle higher-order modulation by treating each bit position separately, thus resolving the conflict between adaptability to higher-order modulation and design simplicity.
Solution Approach 2:
The patent applies different code rates to different bit levels based on their specific channel conditions. Each bit level is assigned a code rate optimized for its effective channel, allowing local optimization without complicating the overall system design. This resolves the contradiction by making the system adaptable to higher-order modulation while maintaining manageable complexity through localized code rate selection.
2Reliability
If different code rates are used for each bit level, then error rates can be balanced across bit levels, but the encoding and decoding complexity increases
Solution Approach 1:
The patent changes the code rate parameter for each bit level to optimize error rate performance. By selecting appropriate code rates for each bit level based on effective channel conditions, the system achieves balanced error rates across all bit levels. The complexity is managed by using standard binary polar code structures with varying rates rather than fundamentally changing the coding mechanism.
3Device complexity
If binary alphabet polar codes are used with higher-order modulation, then low-complexity encoding and decoding can be achieved, but the output bits experience different effective channels
Solution Approach 1:
The patent applies different code rates to different bit levels based on their specific effective channel conditions. This local optimization ensures that each bit level is protected according to its actual channel quality, thereby achieving reliability without significantly increasing complexity, as binary polar codes remain the underlying structure.
Data Source
AI summary
A method includes receiving multiple bits to be transmitted. The method also includes applying a first binary alphabet polar code to a first subset of the multiple bits to generate first encoded bits. The first encoded bits are associated with a first bit level of a multilevel coding scheme. The method further includes generating one or more symbols using the first encoded bits and bits associated with a second bit level of the multilevel coding scheme. The first binary alphabet polar code is associated with a first coding rate. In addition, the method could include applying a second binary alphabet polar code to a second subset of the multiple bits to generate second encoded bits. The second encoded bits are associated with the second bit level. The second binary alphabet polar code is associated with a second coding rate such that the bit levels have substantially equal error rates.