Polar Code Bit Allocation Using Grouped Channel Reliability
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Solution Overview
Problem
Existing encoding and decoding techniques, particularly in wireless communications, face challenges in efficient bit allocation among channel instances, leading to high computational complexity and resource usage, especially when using error-correcting codes like polar codes.
Innovation Solution
The proposed method involves recursively polarizing channel instances into groups and allocating information bits based on reliability metrics, using a base sequence to determine bit locations, and employing these allocations for encoding and decoding operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If polar coding techniques are used to achieve reliable transmission, then transmission reliability is improved, but computational complexity and storage requirements increase
Solution Approach 1:
The channel instances are divided into multiple groups, where each group contains a subset of channel instances. This segmentation allows the encoder to process and allocate bits to smaller manageable groups rather than handling all channel instances individually, thereby reducing computational complexity while maintaining the reliability benefits of polar coding.
Solution Approach 2:
Different groups of channel instances are allocated different numbers of information bits based on their specific reliability characteristics. Instead of uniform allocation, the system applies local quality optimization by matching bit allocation to the actual performance of each group, improving overall transmission reliability while avoiding unnecessary computational overhead in less critical groups.
2Reliability
If polar coding techniques are used to achieve reliable transmission, then transmission reliability is improved, but storage requirements increase
Solution Approach 1:
By segmenting channel instances into groups, the system only needs to store and manage allocation information for each group rather than for every individual channel instance. This significantly reduces the storage requirements while preserving the reliability advantages of polar coding through group-level optimization.
3Device complexity
If uniform bit allocation is used among channel instances, then device complexity is reduced, but transmission reliability deteriorates
Solution Approach 1:
The system implements non-uniform bit allocation within groups based on the reliability characteristics of each group. This local quality approach ensures that more reliable channel instances receive more information bits, improving transmission reliability while keeping the allocation process manageable through the grouping structure.
Data Source
AI summary
Methods, systems, and devices for encoding and decoding are described. To encode a vector, an encoder allocates information bits of the vector to channel instances of a channel that are separated into groups. The groups may vary in size and allocation of the information bits is based on a base sequence of a given length. During decoding, a decoder assigns different bit types to channels instances by dividing a codeword into a plurality of groups and assigning bit types to channel instances of the plurality of groups using the base sequence.