Data Bus Inversion Encoding 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 do not effectively address these issues, particularly when 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 on parallel channels, where a DBI bit is used to identify and restore inverted data bits, thereby reducing ISI, crosstalk, and SSN, and improving power efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data bits are transmitted on parallel channels without encoding, then transmission speed is maintained, but inter-symbol interference (ISI), crosstalk, and simultaneous switching noise (SSN) alter the amplitude and timing of data bits
Solution Approach 1:
The patent applies Data Bus Inversion (DBI) encoding that dynamically changes the state parameters of data bits based on transition detection. When excessive transitions are detected on parallel channels, the encoding inverts the data bits to reduce simultaneous switching events, thereby mitigating SSN, ISI, and crosstalk effects while maintaining signal integrity
Solution Approach 2:
The core DBI mechanism inverts data bits under specific conditions to reduce harmful effects. By detecting when data bit transitions exceed a threshold and inverting the bits before transmission, the system reduces simultaneous switching noise and inter-symbol interference, then uses a DBI indicator bit to enable correct reconstruction at the receiver
2Reliability
If Data Bus Inversion encoding is applied to reduce ISI, crosstalk, and SSN, then signal quality improves, but power consumption increases due to additional encoding and decoding operations
Solution Approach 1:
The system applies DBI encoding selectively rather than continuously. By monitoring data bit transitions and only inverting bits when transition counts exceed a threshold, the patent reduces unnecessary encoding operations, thereby lowering power consumption while still achieving signal quality improvement when needed
Solution Approach 2:
The encoding dynamically adjusts its behavior based on transition parameters. When transition counts are low, no encoding is applied; when transitions exceed the threshold, inversion encoding is activated. This parameter-based control optimizes the balance between signal quality and power consumption
3Use of energy by moving object
If minimum transitions algorithm is used for encoding, then power consumption is reduced, but encoding effectiveness is insufficient when data bits are serialized in packets with no correlation between packets
Solution Approach 1:
The patent segments the data transmission into packets and applies DBI encoding independently to each packet. By resetting the transition count at packet boundaries and treating each packet as an independent unit, the system maintains encoding effectiveness even when packets are serialized without inter-packet correlation, while still reducing power consumption through selective encoding
Solution Approach 2:
The system performs preliminary detection of transition patterns within each packet before applying encoding. By counting transitions at the start of each packet and determining whether encoding is needed based on this preliminary analysis, the system avoids unnecessary encoding operations and maintains effectiveness for packetized data
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.