The relentless growth of data traffic, fueled by cloud computing, AI, and streaming services, is pushing optical communication infrastructure to its limits. This creates immense pressure on manufacturers and operators to deliver higher performance and reliability at lower costs. Efficient, accurate, and cost-effective evaluation of optical modulators is paramount to meet these demands, ensuring the integrity of next-generation networks and data centers.
Could reduce capital expenditure by ~60% compared to conventional complex and expensive dedicated evaluation equipment, by utilizing general-purpose photodetectors (PD) and analog-to-digital converters (ADC).
Applies phase retrieval to estimate electrical-to-optical response imbalance between I/Q channels of optical IQ modulators with higher precision and speed than conventional methods.
Utilizes intensity information from optical modulator output signals, allowing integration into existing optical communication device manufacturing inspection processes with minimal modification.
This patent protects a system for estimating electrical-to-optical response imbalance in optical IQ modulators using general-purpose photodetectors and ADCs, leveraging a phase retrieval algorithm. The claims were robustly established through multiple rejections, demonstrating strong novelty and inventiveness against eight prior art references, indicating a highly stable and difficult-to-invalidate right.
This patent primarily covers the evaluation methodology for optical modulators. White space exists in developing novel optical modulator designs or integrating this evaluation into a comprehensive, AI-driven network diagnostic and self-optimization system.
In the optical modulator evaluation process, assuming conventional dedicated evaluation equipment has annual depreciation/maintenance costs of ~$130K (AI est.) and specialized operator labor costs of ~$65K (AI est.). Implementing this technology could reduce equipment-related costs by 50% (~$65K (AI est.)) through simplified equipment use, and labor costs by 20% (~$15K (AI est.)) due to reduced evaluation time. This projects a total annual cost reduction of ~$80K (AI est.).
X: Cost Efficiency
Y: Evaluation Precision & Speed