Command Bus Training Using Continuous PRBS Patterns
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Solution Overview
Problem
Existing command bus training (CBT) methods for memory systems, such as LPDDR6, are inadequate due to their inability to effectively address inter-symbol interference (ISI), cross-talk, and voltage noise at high speeds, leading to degraded system performance.
Innovation Solution
Implementing a continuous long burst pseudo-random binary sequence (PRBS) pattern for the command address (CA) signal during CBT, which allows for more exhaustive training and improved accuracy in signaling, thereby addressing ISI, cross-talk, and voltage noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing CBT methods are used for memory systems, then the training process can be completed, but the system performance is degraded due to inability to effectively address inter-symbol interference, cross-talk, and voltage noise at high speeds
Solution Approach 1:
The patent applies preliminary action by performing command bus training using continuous long burst PRBS patterns before normal memory operations begin. This pre-training process characterizes and compensates for ISI, cross-talk, and voltage noise effects in advance, allowing the system to operate at high speeds without performance degradation during actual memory transactions.
Solution Approach 2:
The patent changes the training signal parameters by using continuous long burst PRBS patterns instead of traditional training sequences. This parameter change enables the training process to effectively capture and compensate for high-speed signal integrity issues including inter-symbol interference, cross-talk, and voltage noise, thereby improving system performance.
2Measurement precision
If traditional training sequences are used for CBT, then the training can be performed, but the training coverage and accuracy are insufficient due to inability to address high-speed signal integrity issues
Solution Approach 1:
The patent changes the training signal from traditional sequences to continuous long burst PRBS patterns. This parameter change provides superior training accuracy for high-speed operations while the PRBS structure itself remains mathematically well-defined and implementable, balancing accuracy improvement with manageable complexity.
Data Source
AI summary
Various aspects of the present disclosure generally relate to memory devices. In some aspects, a volatile memory device may receive, from a host device, a clock (CK) signal. The memory device may receive, from the host device, a command address (CA) signal associated with a continuous long burst pseudo-random binary sequence (PRBS) pattern. The memory device may perform a command bus training (CBT) based at least in part on the CA signal in relation to the CK signal. The memory device may provide, to the host device, pass or fail results associated with the CBT. Numerous other aspects are described.