Distribution Matching for Flexible Low-Power Data Streaming
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Solution Overview
Problem
Existing data signal conversion and transmission methods face challenges in achieving high reliability and low power consumption, especially under high data load streaming conditions, with existing variable-to-fixed length distribution matchers being inflexible and complex.
Innovation Solution
A method and system that employ a family of distribution matching functions controlled by selection rules to process input symbol streams, allowing for flexible handling of symbol processing and achieving desired transfer rates and distributions, with the option to perform these processes in a continuously clocked and streaming manner, and incorporating error correction processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a predetermined and fixed variable-to-fixed length distribution matcher is used, then the conversion process is simple, but the system lacks flexibility in handling different data loads and streaming conditions
Solution Approach 1:
The patent implements a dynamic distribution matching system that adapts its behavior based on streaming conditions and data load. The system transitions from fixed predetermined matchers to a dynamic selection mechanism that chooses appropriate distribution matching functions based on current operational parameters, enabling flexibility while managing complexity through conditional logic.
Solution Approach 2:
The system changes operational parameters by selecting different distribution matching functions from a family of functions based on current data load and streaming conditions. This parameter-based selection allows the system to optimize performance for different operating scenarios without requiring a completely different architecture for each condition.
2Productivity
If high data transfer rates are achieved through continuous clocking and streaming processing, then productivity increases, but power consumption increases
Solution Approach 1:
The patent employs periodic action by using continuous clocking and streaming processing only when high data transfer rates are required. The system can switch between different operational modes, using the power-intensive continuous processing periodically or conditionally rather than continuously, thereby achieving high productivity when needed while reducing average power consumption.
3Adaptability or versatility
If a family of distribution matching functions with selection rules is implemented, then adaptability to different data loads improves, but device complexity increases
Solution Approach 1:
The patent segments the distribution matching functionality into a family of distinct distribution matching functions, each optimized for specific data load conditions. The selection rules act as a segmentation mechanism that routes input data to the appropriate function based on current conditions, improving adaptability while managing complexity through structured organization.
Solution Approach 2:
The selection rules serve as an intermediary layer between the input data and the family of distribution matching functions. This intermediary component manages the complexity by providing a systematic method for choosing the appropriate function based on data load characteristics, shielding the user from the underlying complexity while maintaining adaptability.
Data Source
AI summary
Methods (C) for converting a data signal (U), comprising processes of (i) providing an input symbol stream (IB) of input symbols (IBj), the input symbol stream (IB) being representative for the underlying data signal (U) to be converted, and (ii) applying a distribution matching process to consecutive partial input symbol sequences (IBk) of a number of k consecutive input symbols (IBj) covering said input symbol stream (IB). The distribution matching process (DM) generates and outputs a final output symbol stream (OB) of consecutive output symbols (OBj) or a preform thereof, wherein the distribution matching process (DM) is based on and/or comprises a family ((ƒi)i∈{0, 1, . . . , n-1}) of a number (n) of distribution matching functions (ƒi), the action of the distribution matching process (DM) is achieved by acting with one of said distribution matching functions (ƒi) selected from said family ((ƒi)i∈{0, 1, . . . , n-1}) on said partial input symbol sequences (IBk), and wherein selecting a distribution matching function (ƒi) from said family ((ƒi)i∈{0, 1, . . . , n-1}) is based on a set of rules comprising at least one selection rule.