This inventor holds 1 USPTO granted patent. Top assignee: Nokia Solutions and Networks Oy. Active years: 2026.
Company Filing History:
Years Active: 2026
Title: Innovations of Jiaqi Quan in Machine Learning for Channel Estimation
Introduction
Jiaqi Quan is an accomplished inventor based in Shanghai, China. He has made significant contributions to the field of machine learning, particularly in channel estimation techniques. His innovative approach addresses the challenges posed by diverse Doppler effects, enhancing communication systems' efficiency.
Latest Patents
Jiaqi Quan holds a patent titled "Machine learning for channel estimation against diverse Doppler effects." This patent describes a method where a first device receives user data from a second device via a communication channel. The user data includes a reference symbol, which is crucial for the channel estimation process. The first device utilizes a neural network (NN) to perform an initial channel estimation based on the velocity information of the second device and the results of a secondary channel estimation. This innovative solution allows for effective channel estimation in various scenarios, including high-velocity conditions, while minimizing overhead in reference signals.
Career Highlights
Jiaqi Quan is currently employed at Nokia Solutions and Networks Oy, where he continues to develop cutting-edge technologies in telecommunications. His work focuses on improving network performance and reliability through advanced machine learning techniques. With a patent portfolio that includes 1 patent, he is recognized for his contributions to the industry.
Collaborations
Jiaqi has collaborated with notable colleagues, including Wenliang Qi and Wenyi Xu, who have also contributed to advancements in their respective fields. Their teamwork fosters an environment of innovation and creativity, leading to impactful developments in technology.
Conclusion
Jiaqi Quan's work in machine learning for channel estimation exemplifies the potential of innovative technologies to transform communication systems. His contributions not only enhance network efficiency but also pave the way for future advancements in the field.