Transmitter Data Transmission Using Sign Bit Shaping
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Solution Overview
Problem
Existing communication systems face challenges in efficiently transmitting data using non-symmetric distributions, as existing methods are not adapted to consider sign bits as shaping bits, leading to suboptimal performance and complexity in combining probabilistic shaping with error-correcting codes.
Innovation Solution
A method for transmitting data using a constellation with M = 2^m symbols divided into N sub-constellations, where each symbol in a reference sub-constellation has a corresponding symbol in other sub-constellations with the same probability, employing systematic error-correcting codes and distribution matchers that treat sign bits as shaping bits, allowing for non-symmetric distributions and improved energy efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing error-correcting code methods are used with symmetric distributions, then the parity bit has equiprobable distribution, but the method is not adapted to non-symmetric distributions and cannot treat sign bits as shaping bits
Solution Approach 1:
The constellation is segmented into N sub-constellations, each associated with a unique parity bit pattern. This segmentation allows the system to handle non-symmetric distributions by mapping specific sub-constellations to specific parity patterns, thereby resolving the contradiction between adaptability and complexity.
Solution Approach 2:
The invention introduces a new dimension by treating sign bits as shaping bits in addition to magnitude bits. This dimensional extension allows distribution matchers to operate on all bits uniformly, enabling non-symmetric distributions while maintaining systematic error-correcting code structure.
2Use of energy by moving object
If uniformly distributed symbols are transmitted, then the transmission is simple, but there is an absence of shaping gain and energy efficiency
Solution Approach 1:
The invention changes the probability distribution parameter of transmitted symbols from uniform to non-uniform by using distribution matchers. These matchers transform uniformly distributed input bits into shaped output symbols according to a target distribution, achieving energy efficiency gains while maintaining manageable complexity through systematic implementation.
3Loss of energy
If probabilistic shaping is applied to approach channel capacity, then energy savings are achieved, but the combination with error-correcting code becomes complex
Solution Approach 1:
The invention creates a universal framework where systematic error-correcting codes and distribution matchers work together through a unified bit-grouping mechanism. By organizing bits into groups that identify symbols in reference sub-constellations and using parity bits to identify transmitted sub-constellations, the system achieves both shaping gain and error correction with reduced complexity.
Data Source
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AI summary
A method, in a transmitter, is disclosed The method is for transmitting data using a constellation with M = 2m symbols, divided in N sub-constellations, N and M being integers, where for any symbol in a reference sub-constellation, there is a symbol in each of the other sub-constellations with a same probability value. The method comprises: - obtaining (S100) from a source of data, k groups of m - log2(N) shaping bits wherein each group of m - log2(N) shaping bits identifies one symbol xj in the reference sub-constellation, j∈[1;k] ; - applying (S104) a systematic error correcting code on said k groups of m-log2(N) shaping bits to output one group of log2(N) parity bits per each symbol xj ; - for each symbol xj, identifying (S106) a sub-constellation using at least the group of log2(N) parity bits and selecting a symbol identified by said m-log2(N) shaping bits in said identified sub-constellation; and - transmitting (S108) each of said k selected symbols to a receiver over a communication channel.