ADC Interface Rate Adaptation for Low-Latency Control Streams
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Solution Overview
Problem
Traditional systems face challenges in effectively managing and delivering disparate-rate data streams and sub-streams for processing, leading to inefficiencies and increased latency in controlling components like camera motors in mobile devices.
Innovation Solution
A system comprising a processing engine and an analog-to-digital conversion interface subsystem that processes feedback data to generate digital control signals, reducing latency by modifying the output sample rate and optimizing the generation of control signals for systems under control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional systems manage disparate-rate data streams using standard processing methods, then system complexity is reduced, but latency increases and processing efficiency deteriorates
Solution Approach 1:
The patent segments the data stream management into multiple parallel processing pipelines, each handling specific data streams at their native rates. The system divides incoming disparate-rate data streams into separate channels that can be processed independently, then recombines them after processing. This segmentation allows each pipeline to operate optimally without being constrained by other streams' rate requirements, reducing overall latency while maintaining manageable complexity through modular architecture.
Solution Approach 2:
The patent implements dynamic rate adaptation mechanisms where the system adjusts processing rates and buffer sizes in real-time based on incoming data characteristics and processing demands. The architecture allows processing engines to dynamically scale their operation rates and the system to flexibly allocate resources between different data streams. This dynamic behavior enables the system to handle variable-rate streams efficiently without fixed complexity constraints, minimizing latency through adaptive optimization.
2Productivity
If data streams are processed at their native disparate rates, then processing efficiency is improved, but system complexity increases due to rate synchronization requirements
Solution Approach 1:
The patent introduces intermediary buffer structures and rate-adaptation layers that act as mediators between disparate-rate data streams and the processing engines. These intermediaries absorb rate variations and perform rate conversion, allowing upstream streams to produce at their native rates while downstream processors consume at their optimal rates. The intermediary layer handles the synchronization complexity independently, enabling efficient parallel processing of multiple streams without direct complex coordination between all components.
Solution Approach 2:
The patent employs parameter transformation techniques where data streams undergo rate conversion, buffer depth adjustment, and timing parameter modification as they pass through the system. Each data stream's parameters (rate, timing, buffering) are dynamically adjusted to match processing requirements while maintaining data integrity. This parameter flexibility allows efficient processing at native rates to be achieved while managing synchronization through controlled parameter changes rather than rigid rate matching.
3Speed
If latency is minimized through optimized processing, then control responsiveness is improved, but flexibility in managing disparate rates deteriorates
Solution Approach 1:
The patent implements dynamic processing pipelines that can adjust their speed and buffering characteristics in real-time based on the specific requirements of each data stream and the overall system state. The system maintains multiple processing paths with variable latency characteristics, allowing it to optimize for speed when needed while preserving the ability to handle rate variations. This dynamic adaptability enables the system to achieve low latency for time-critical control while maintaining flexibility for managing disparate-rate streams through configurable processing parameters.
Data Source
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AI summary
A system may include a processing engine and an analog-to-digital conversion interface subsystem communicatively coupled to the processing engine. The processing engine may be configured to process feedback data converted from analog feedback data to digital feedback data, wherein the feedback data includes a plurality of data stream sequences converted from the analog feedback data to the digital feedback data at a sample rate and based on processing of the feedback data, generate digital control signals for controlling a system under control. The analog-to-digital conversion interface subsystem may be configured to flexibly control the processing of the processing engine and the generation of digital control signals by the processing engine to minimize latency in the generation of the digital control signals due to processing of the processing engine.