Data Bus Inversion Encoding to Reduce Simultaneous Switching Noise
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Solution Overview
Problem
Simultaneous switching noise (SSN) occurs in integrated circuit communication due to multiple output drivers changing states at high speeds, causing power supply disturbances and undesired transient behavior.
Innovation Solution
A data encoding scheme that combines dynamic bus inversion (DBI) and non-DBI encoding, using a data mask signal to indicate the type of encoding, which reduces SSN by limiting Hamming Weights of encoded data to a small range, thereby minimizing transmitter and receiver switching transitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If multiple output drivers change state simultaneously to transmit multi-bit data at high speed, then data transmission speed is improved, but power supply disturbance (SSO noise) increases
Solution Approach 1:
The patent changes the parameter of data encoding by applying data bus inversion (DBI) selectively based on Hamming Weight thresholds. By transforming the data representation and controlling the number of switching transitions through encoding parameters, the patent reduces simultaneous switching noise while maintaining high-speed data transmission capability.
Solution Approach 2:
The patent implements dynamic encoding selection where the encoding method (DBI or non-DBI) is dynamically chosen based on the Hamming Weight of the data being transmitted. This dynamic adaptation allows the system to optimize between transmission efficiency and noise reduction in real-time, preventing power supply disturbance during high-speed operation.
2Object-generated harmful factors
If data bus inversion is applied to reduce SSN, then power supply disturbance is reduced, but encoding complexity increases
Solution Approach 1:
The patent segments the data transmission process into distinct encoding paths: DBI encoding for data with Hamming Weight below the threshold, and non-DBI encoding for data above the threshold. This segmentation allows the system to apply complexity only when necessary (DBI encoding) while using simpler encoding for other cases, thereby reducing overall encoding complexity while still achieving SSN reduction.
Solution Approach 2:
The patent applies different encoding qualities locally based on data characteristics. Instead of uniformly applying DBI encoding to all data, the system applies DBI encoding only to specific data segments (those with Hamming Weight below threshold), making the encoding process more efficient and less complex while maintaining effectiveness in reducing SSN.
3Object-generated harmful factors
If Hamming Weight is limited to reduce SSN, then power supply disturbance is minimized, but data encoding complexity increases
Solution Approach 1:
The patent uses Hamming Weight as a controllable parameter to determine encoding strategy. By setting a threshold parameter for Hamming Weight, the system automatically adjusts the encoding approach to limit switching transitions, thereby minimizing power supply disturbance while managing encoding complexity through parameter-based control rather than complex algorithms.
Data Source
AI summary
A data encoding scheme for transmission of data from one circuit to another circuit combines DBI encoding and non-DBI encoding and uses a data mask signal to indicate the type of encoding used. The data mask signal in a first state indicates that the data transmitted from one circuit to said another circuit is to be ignored, and the data mask signal in a second state indicates that the data transmitted from one circuit to said another circuit is not to be ignored. If the data mask signal is in the second state, a first subset of the data is encoded with data bus inversion and a second subset of the data is encoded differently from data bus inversion. Such encoding has the advantage that SSO noise is dramatically reduced when the encoded data is transmitted from one circuit to another circuit.