Mutual-Information Polar Code Construction for Punctured Bit-Channels
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Solution Overview
Problem
Polar codes in wireless communication systems face challenges in accommodating puncturing, leading to reduced throughput due to the inability to account for punctured bits, which affects the allocation of information bits to bit-channels based on reliability metrics.
Innovation Solution
A method for encoding and decoding polar codes that identifies punctured bit locations and adjusts the initial target mutual information and recursive partitioning to account for the number of punctured bits, ensuring information bits are allocated to the most reliable bit-channels, using a mutual information transfer function to determine bit-channel capacities and allocate bits effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If polar codes use fixed encoder lengths determined by a power function, then the code structure is simple and standardized, but the system cannot flexibly accommodate variable bit rates and puncturing scenarios
Solution Approach 1:
The patent implements dynamic code construction by allowing the encoder length and bit-channel partitioning to adapt based on the number of punctured bits. The system dynamically adjusts the target mutual information and re-partitions bit-channels at each polarization stage according to actual puncturing patterns, transforming a static code structure into a dynamic one that responds to channel conditions and puncturing requirements.
Solution Approach 2:
The patent changes key parameters including the target mutual information value and the partitioning configuration of bit-channels based on the number of punctured bits. By modifying these parameters dynamically, the system adapts the polar code construction to accommodate variable bit rates and puncturing scenarios while maintaining optimal performance.
2Productivity
If punctured bits are not accounted for in polar code encoding, then the encoding process is simple, but information bits are incorrectly allocated to unreliable bit-channels reducing throughput
Solution Approach 1:
The patent performs preliminary identification of punctured bit locations and adjusts the target mutual information before the actual encoding process. By preparing the bit-channel partitioning and reliability metrics in advance based on known puncturing patterns, the system ensures that information bits are correctly allocated to reliable bit-channels without requiring complex real-time adjustments during encoding.
Solution Approach 2:
The system uses feedback about the number and positions of punctured bits to adjust the encoding process. The decoder information about punctured bits is fed back to the encoder side, allowing the system to modify the target mutual information and bit-channel partitioning accordingly, ensuring optimal throughput performance.
3Measurement precision
If the target mutual information is not adjusted for punctured bits, then the calculation is simpler, but the allocation of information bits to bit-channels becomes inaccurate
Solution Approach 1:
The patent dynamically changes the target mutual information parameter based on the number of punctured bits. The formula adjusts the target mutual information by incorporating the ratio of un-punctured bits to total bits, ensuring accurate bit-channel capacity measurement that reflects the actual transmission conditions.
4Adaptability or versatility
If polar codes accommodate flexible bit rates and puncturing, then the system is more versatile, but the number of bits required to describe each code structure increases
Solution Approach 1:
The patent uses parameter changes to achieve flexibility, where the target mutual information and bit-channel partitioning are adjusted based on the number of punctured bits. This approach allows the system to support a wide range of code rates and lengths by dynamically modifying parameters rather than requiring separate code structures for each scenario.
Data Source
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AI summary
Methods, systems, and devices for wireless communication are described. To encode a vector of bits using a polar code, an encoder may allocate information bits of the vector to polarized bit-channels associated with a channel (e.g., a set of unpolarized bit-channels) used for a transmission. In some cases, the polarized bit-channels may be partitioned into groups associated with different values of some associated reliability metric (s). The information bits may be allocated to the polarized bit-channels based on the reliability metrics of the different polarized bit-channels and the overall capacity of a transmission. That is, the bit locations of a transmission may depend on the reliability metrics of different polarized bit-channels and the overall capacity of the transmission. To facilitate puncturing, the overall capacity of the transmission may be adjusted and the unpolarized bit-channels may be partitioned into polarized bit-channels based on the adjusted capacity.