Adaptive Data Bus Inversion Encoding for Noise-Limited Links
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Solution Overview
Problem
Data transmission in integrated circuit devices is affected by inter-symbol interference (ISI), crosstalk, and simultaneous switching noise (SSN), and existing encoding techniques like the minimum transitions algorithm do not effectively address these issues, particularly in scenarios where data bits are serialized and lack correlation between packets, leading to inefficient power consumption.
Innovation Solution
Implementing multiple Data Bus Inversion (DBI) algorithms, such as minimum transitions, minimum zeros, and minimum ones, to encode data bits across parallel channels, using a separate DBI bit to identify inverted data and restore them at the receiver, thereby reducing ISI, crosstalk, and SSN, while optimizing power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data bits are transmitted over parallel channels without encoding, then transmission speed is maintained, but signal quality deteriorates due to inter-symbol interference, crosstalk, and simultaneous switching noise
Solution Approach 1:
The patent applies parameter changes by dynamically selecting between multiple DBI algorithms (minimum transitions, minimum zeros, minimum ones) based on the characteristics of the data to be transmitted. This allows the encoding scheme to adapt to different data patterns and transmission conditions, optimizing signal quality while managing complexity through selective algorithm application rather than using a single fixed encoding method
Solution Approach 2:
The system implements dynamics by using different DBI algorithms for different cycles or data packets. The encoder can switch between minimum transitions algorithm, minimum zeros algorithm, and minimum ones algorithm depending on the data characteristics, creating a dynamic encoding system that responds to varying transmission conditions rather than using a static encoding approach
2Use of energy by moving object
If minimum transitions algorithm is used for encoding, then power consumption is reduced, but encoding effectiveness deteriorates when data bits lack correlation between packets
Solution Approach 1:
The system implements dynamics by using different DBI algorithms for different cycles or data packets. The encoder can switch between minimum transitions algorithm, minimum zeros algorithm, and minimum ones algorithm depending on the data characteristics, creating a dynamic encoding system that responds to varying transmission conditions rather than using a static encoding approach
Solution Approach 2:
The patent applies parameter changes by dynamically selecting between multiple DBI algorithms (minimum transitions, minimum zeros, minimum ones) based on the characteristics of the data to be transmitted. This allows the encoding scheme to adapt to different data patterns and transmission conditions, optimizing signal quality while managing complexity through selective algorithm application rather than using a single fixed encoding method
3Reliability
If multiple DBI algorithms are implemented, then encoding effectiveness improves, but device complexity increases
Solution Approach 1:
The patent applies parameter changes by dynamically selecting between multiple DBI algorithms (minimum transitions, minimum zeros, minimum ones) based on the characteristics of the data to be transmitted. This allows the encoding scheme to adapt to different data patterns and transmission conditions, optimizing signal quality while managing complexity through selective algorithm application rather than using a single fixed encoding method
Solution Approach 2:
The encoding function is segmented into multiple specialized algorithms (minimum transitions, minimum zeros, minimum ones), each handling specific data patterns effectively. Rather than one complex algorithm trying to handle all cases, the system divides the encoding task into multiple simpler specialized algorithms that can be selected based on data characteristics, making the overall system more manageable
Data Source
AI summary
Apparatus, systems, and methods are disclosed such as those that operate to encode data bits transmitted on a plurality of channels according to at least one of multiple Data Bus Inversion (DBI) algorithms. Additional apparatus, systems, and methods are disclosed.