Adaptive Polarization Weighting for Scalable Polar Code Bit Distribution
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Solution Overview
Problem
Existing algorithms for polar code construction are computationally inefficient and introduce undesirable features, making them suboptimal for allocating frozen and information bits in polar codes.
Innovation Solution
The method involves determining the reliability of each bit position by calculating weighted summations based on a binary expansion, using an enhanced Polarization Weighting (PW) approach that adjusts the expansion factor based on the coding rate and block size to improve the accuracy of information bit allocation, thereby optimizing the distribution of bits in polar codes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing algorithms for polar code construction are used, then the construction process can be completed, but computational efficiency is poor and undesirable features are introduced
Solution Approach 1:
The patent modifies the polarization weighting calculation by changing the expansion factor from a fixed value to a variable that adapts based on coding rate and block size. This parameter change enables the algorithm to achieve both computational efficiency and accurate bit allocation by adjusting the weighting scheme to match specific code construction requirements, resolving the contradiction between speed and accuracy.
Solution Approach 2:
The invention introduces dynamic adaptation in the polarization weighting process by making the expansion factor variable rather than static. The algorithm dynamically adjusts weighting parameters based on the specific code rate and block size being constructed, allowing it to maintain high computational efficiency while achieving desirable bit allocation characteristics for different code configurations.
2Ease of manufacture
If fixed expansion factor methods are used, then computational simplicity is maintained, but accuracy of information bit allocation deteriorates
Solution Approach 1:
The patent transitions from a static expansion factor to a dynamic one that adapts to coding rate and block size. This maintains computational simplicity through a straightforward calculation formula while significantly improving reliability determination accuracy by adjusting the expansion factor based on specific code parameters, thus resolving the contradiction between ease of implementation and measurement precision.
3Adaptability or versatility
If scalability is not enhanced, then existing methods can be applied, but limitations such as finite precision effects persist
Solution Approach 1:
The invention enhances scalability by introducing parameter-adaptive expansion factors that change based on coding rate and block size. This allows the algorithm to maintain high performance and avoid finite precision effects across a wide range of code configurations, resolving the contradiction between broad applicability and reliable performance under varying conditions.
Data Source
AI summary
Methods and devices are described for determining reliabilities of bit positions in a bit sequence for information bit allocation using polar codes. The reliabilities are calculated using a weighted summation over a binary expansion of each bit position, wherein the summation is weighted by an exponential factor that is selected based at least in part on the coding rate of the polar code. Information bits and frozen bits are allocated to the bit positions based on the determined reliabilities, and data is polar encoded as the information bits. The polar encoded data is then transmitted to a remote device.