Channel Training for Optical Network Unit Registration
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Solution Overview
Problem
In high-speed passive optical networks, newly added optical network units (ONUs) face challenges in registering and going online due to high bit error rates and power penalties resulting from deteriorated optical signal performance during transmission in existing fibers.
Innovation Solution
A channel training method is introduced, where a training frame is generated and sent to all ONUs, allowing the automatic adaptive equalizer to optimize its operation, reducing bit error rates and power penalties by bypassing certain coding and scrambling modules to ensure correct training sequence reception.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a 10G low-speed optical device is used to send and receive 25 Gbps data in NGEPON, then bandwidth is improved, but performance of the high-speed optical signal deteriorates and bit error rate increases
Solution Approach 1:
The patent applies preliminary action by performing channel training before normal data transmission. The OLT sends training frames containing equalization coefficients to the ONU in advance, allowing the ONU to pre-adjust its automatic adaptive equalizer parameters. This preliminary adjustment optimizes the optical signal reception performance before actual high-speed data transmission begins, thereby reducing bit error rates while maintaining the improved bandwidth capability.
2Productivity
If a newly added ONU is integrated into the PON, then network capacity is improved, but the ONU cannot register and go online in time due to high bit error rates
Solution Approach 1:
The patent implements preliminary action by establishing a channel training mechanism that activates when a new ONU joins the network. The OLT detects the new ONU and immediately initiates training frame transmission with pre-calculated equalization coefficients tailored to that specific ONU's channel characteristics. This allows the new ONU to quickly optimize its receiver parameters and register with the network without experiencing the high bit error rates that would otherwise delay its online status, thus maintaining improved network capacity while reducing registration time loss.
Data Source
AI summary
The present disclosure relates to the field of communications technologies, and discloses a channel training method, apparatus, and system, so as to resolve a problem in which a newly added ONU in a PON cannot be registered and go online in time. In embodiments of the present disclosure, a first moment for triggering channel training is determined; normal data is stopped sending from the first moment and a training frame is generated; and then the training frame is sent to all ONUs in a PON, so that a target ONU trains an automatic adaptive equalizer based on the training frame, where the target ONU is at least one of all the ONUs in the PON. The solutions provided in the embodiments of the present disclosure are applicable to the equalizer training the ONU.