Distribution Matching Conversion for Low-Power Reliable Data Transmission
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Solution Overview
Problem
Existing data signal conversion and transmission methods face challenges in achieving high reliability with reduced power consumption, as they often require complex processes and large alphabets that increase power usage and complexity.
Innovation Solution
The method involves demultiplexing an input symbol stream into partial streams, applying distribution matching processes with smaller alphabets to generate pre-sequences, and then using symbol mapping to create a final output sequence, with the option for invertible processes and variable symbol lengths to enhance efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex conversion processes and large alphabets are used, then data transmission reliability is improved, but power consumption increases
Solution Approach 1:
The input symbol stream is demultiplexed into multiple partial symbol streams, which are then processed by separate distribution matching processes. This segmentation allows each process to work with smaller alphabets, reducing power consumption while maintaining overall transmission reliability through the combined output.
Solution Approach 2:
The invention changes the parameter of alphabet size from large to small by using multiple distribution matching processes with smaller individual alphabets instead of one process with a large alphabet. This parameter change reduces the complexity and power consumption of each individual process while achieving the same overall functionality.
2Use of energy by moving object
If smaller alphabets are used in distribution matching processes, then power consumption is reduced, but the complexity of the overall system increases
Solution Approach 1:
The system is segmented into multiple distribution matching processes, each handling a portion of the data with a smaller alphabet. While the number of processes increases, each individual process remains simple, and the overall system complexity is managed through the structured demultiplexing and multiplexing framework.
Solution Approach 2:
The invention transitions from a single-dimensional approach (one distribution matching process with large alphabet) to a multi-dimensional approach (multiple processes with smaller alphabets). This dimensional change allows the system to distribute the computational load across multiple simpler processes, reducing the complexity of each individual component.
3Productivity
If variable symbol lengths are used, then processing efficiency is improved, but the complexity of symbol mapping increases
Solution Approach 1:
The symbol mapping process is made dynamic by allowing variable output symbol lengths from the distribution matching processes. This dynamic approach enables the system to adapt to different data patterns and optimize processing efficiency, with the symbol mapping process adjusting its behavior based on the input characteristics.
Solution Approach 2:
The invention changes the parameter of symbol length from fixed to variable, allowing the distribution matching processes to output sequences of different lengths. This parameter change enables more efficient processing by adapting to the specific requirements of different data segments, while the symbol mapping process handles the variability through its flexible design.
Data Source
AI summary
A method (C) for converting a data signal (U), comprising (i) providing an input symbol stream (B) representative of the data signal (U), (ii) demultiplexing (DMX) the input symbol stream (B) to consecutively decompose the input symbol stream (B) into a number m of decomposed partial symbol streams (B_1, . . . , B_m), (iii) applying on each of the decomposed partial symbol streams (B_1, . . . , B_m) an assigned distribution matching process (DM_1, . . . , DM_m), thereby generating and outputting for each decomposed partial symbol stream (B_1, . . . , B_m) a respective pre-sequence (bn_1, . . . , bn_m) or n_j symbols as an intermediate output symbol sequence, and (iv) supplying the pre-sequences (bn_1, . . . , bn_m) to at least one symbol mapping process (BM) to generate and output a signal representative for a final output symbol sequence (S) as a converted data signal. Each of the distribution matching processes (DM_1, . . . , DM_m) and the symbol mapping process (BM) are based on a respective assigned alphabet (ADM_1, . . . , ADM_m; ABM) of symbols, and the cardinality of each of the alphabets (ADM_1, . . . , ADM_m) of the distribution matching processes (DM_1, . . . , DM_m) is lower than the cardinality of the alphabet (ABM) of the symbol mapping process (BM).