Multi-Algorithm Data Bus Inversion for ISI and Crosstalk Control
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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 fail to optimize signal quality and power consumption due to loss of correlation between data packets and neglecting binary state considerations.
Innovation Solution
Implementing multiple Data Bus Inversion (DBI) algorithms, such as minimum transitions, minimum zeros, and minimum ones, to encode data bits on parallel channels, using a separate DBI bit to identify inverted data and restore original states, thereby reducing ISI, crosstalk, and SSN, and improving power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data bits are transmitted without encoding, then transmission speed is maintained, but signal quality deteriorates due to ISI, crosstalk, and SSN
Solution Approach 1:
The patent applies Data Bus Inversion (DBI) encoding that dynamically changes the state of data bits based on transition detection. When excessive transitions are detected, the encoder inverts all data bits on the bus, transforming the signal parameters to reduce ISI and SSN while maintaining transmission timing
Solution Approach 2:
A DBI control signal acts as an intermediary between the data source and receiver. This control signal indicates whether inversion has occurred, allowing the receiver to properly interpret the inverted data bits and restore original signal quality without losing transmission speed
2Use of energy by moving object
If minimum transitions algorithm is used for encoding, then power consumption is reduced, but encoding effectiveness deteriorates due to loss of packet correlation and neglect of binary state
Solution Approach 1:
The patent implements multiple DBI algorithms (minimum transitions, minimum zeros, minimum ones) that can be dynamically selected based on data characteristics. This dynamic adaptation allows the system to optimize for power consumption when appropriate while maintaining encoding effectiveness through algorithm selection based on current data patterns
Solution Approach 2:
The system changes encoding parameters by selecting different DBI algorithms based on detected data patterns. When data shows correlation between packets, minimum transitions algorithm reduces power consumption. When binary state distribution is skewed, minimum zeros or minimum ones algorithms maintain encoding effectiveness by addressing the specific data characteristics
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.