A research team led by Professor Wang Cheng from the Department of Electrical Engineering (EE) at City University of Hong Kong (CityUHK) has developed a world-leading microwave photonic chip that is capable of performing ultrafast analog electronic signal processing and computation using optics.

The chip, which is 1,000 times faster and consumes less energy than a traditional electronic processor, has a wide range of applications, covering areas such as 5/6G wireless communication systems, high-resolution radar systems, artificial intelligence, computer vision, and image/video processing.

The team's research findings have just been published in the prestigious scientific journal Nature, under the title “Integrated Lithium Niobate Microwave Photonic Processing Engine”. It is a collaborative research with The Chinese University of Hong Kong (CUHK).

The team has developed a world-leading MWP chip that is capable of performing ultrafast analog electronic signal processing and computation using optics.

The rapid expansion of wireless networks, the Internet of Things, and cloud-based services has placed significant demands on underlying radio frequency systems. Microwave photonics (MWP) technology, which uses optical components for microwave signal generation, transmission, and manipulation, offers effective solutions to these challenges. However, integrated MWP systems have struggled to achieve ultrahigh-speed analog signal processing with chip-scale integration, high fidelity, and low power simultaneously.

The rapid expansion of wireless networks, the Internet of Things, and cloud-based services has placed significant demands on underlying radio frequency systems. Microwave photonics (MWP) technology, which uses optical components for microwave signal generation, transmission, and manipulation, offers effective solutions to these challenges. However, integrated MWP systems have struggled to achieve ultrahigh-speed analog signal processing with chip-scale integration, high fidelity, and low power simultaneously.

“To address these challenges, our team developed a MWP system that combines ultrafast electro-optic (EO) conversion with low-loss, multifunctional signal processing on a single integrated chip, which has not been achieved before,” explained Professor Wang.

Such performance is enabled by an integrated MWP processing engine based on a thin-film lithium niobate (LN) platform capable of performing multi-purpose processing and computation tasks of analog signals.

“The chip can perform high-speed analog computation with ultrabroad processing bandwidths of 67 GHz and excellent computation accuracies,” said Feng Hanke, PhD student of EE and co-first author of the paper.

The team has been dedicated to the research of the integrated LN photonic platform for several years. In 2018, together with colleagues at Harvard University and Nokia Bell labs, they developed the world's first CMOS (complementary metal-oxide semiconductor)-compatible integrated electro-optic modulators on the LN platform, which laid the foundation for the current research breakthrough. LN is referred to as the “silicon of photonics” for its importance to photonics comparable to silicon in microelectronics.

The chip has a wide range of applications, covering areas such as 5/6G wireless communication systems, high-resolution radar systems, artificial intelligence, computer vision, and image/video processing.

Their work not only opens up a new research field, i.e. LN microwave photonics, enabling microwave photonics chips with compact sizes, high signal fidelity, and low latency; but also represents a chip-scale analog electronic processing and computing engine.

The co-first authors of the paper are Feng Hanke and Ge Tong (EE undergraduate). Professor Wang is the corresponding author. Other contributing authors include Dr Guo Xiaoqing, PhD graduate of EE; Dr Chen Zhaoxi, Dr Zhang Ke, Dr Zhu Sha (also at Beijing University of Technology), Dr Sun Wenzhao (now at CityUHK (Dongguan)), EE postdocs; Zhang Yiwen, EE PhD student; and collaborators (Wang Benshan, Professor Huang Chaoran, and Professor Yuan Yixuan) from CUHK.