Polar Code Interleaving for Noise-Correlated Symbol Mapping
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Solution Overview
Problem
Current digital communication systems face challenges in achieving high coding gain and low power consumption, particularly in high-throughput applications where Forward Error Correction (FEC) blocks consume significant power and existing polar coding techniques do not effectively utilize noise correlation to improve bit error rates.
Innovation Solution
A communication system that employs a polar encoder to encode message bits into encoded sequences, an interleaver to rearrange bits, and a bits-to-symbol mapper to convert these into non-binary symbols, which are then processed and transmitted. The system also includes a receiver with a deinterleaver and polar decoder that benefits from noise correlation to select bit channels as either information or frozen channels based on error probability, optimizing bit error rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional polar coding techniques are used, then encoding can be performed with low complexity, but coding gain is insufficient and bit error rates are not optimized
Solution Approach 1:
The encoded message bits sequence is segmented and rearranged using an interleaver that groups bits based on their channel reliability characteristics. This segmentation allows the system to separate information bits that benefit from noise correlation into specific positions, improving bit error rate without requiring complex adaptive processing during transmission
Solution Approach 2:
The interleaver performs preliminary rearrangement of encoded bits before mapping to non-binary symbols. By pre-organizing bits according to their error probability characteristics and noise correlation patterns, the system prepares the data in an optimal configuration that enables the decoder to exploit noise correlation for improved reliability without adding complexity during real-time processing
2Reliability
If FEC blocks are used for reliable communication, then error correction is achieved, but power consumption increases significantly
Solution Approach 1:
The system changes the parameter of symbol representation from binary to non-binary, and modifies the bit arrangement parameter through interleaving. These parameter changes enable the decoder to exploit noise correlation more effectively, achieving the same communication reliability with reduced redundancy requirements, thereby lowering the computational power needed for FEC operations
3Reliability
If noise correlation is not utilized, then encoding/decoding is simpler, but coding gain and bit error rate performance are suboptimal
Solution Approach 1:
The interleaver acts as an intermediary component that rearranges encoded bits into a configuration that exposes noise correlation patterns. This intermediary structure enables the subsequent non-binary mapper and decoder to exploit noise correlation for improved coding gain, while the interleaver itself maintains a simple, fixed structure that does not significantly increase processing complexity
Data Source
AI summary
The disclosed systems and methods for encoding, by a polar encoder, K message bits into an encoded message bits sequence C(M) using polar codes, where K and M are integer values and M is greater than or equal to K; rearranging, by an interleaver, the encoded message bits sequence C(M) to rearranged encoded message bits sequence C′(M) such that a C(i)th bit and aC(M2+i)th bit of the encoded message bits sequence C(M) are arranged together, where i is an integer value that varies between 1 toM2;mapping, by a bits-to-symbol mapper, the rearranged encoded message bits sequence C(M) to N non-binary symbols, where N is an integer value; and processing, by a transmitter symbol processor, the N non-binary symbols to transmit the processed non-binary symbols towards a receiver.