Zhengya Zhang, assistant professor of Electrical and Computer Engineering, was recently awarded an NSF CAREER grant for his research project, “Removing Energy Barrier towards Capacity-Approaching Information Transmission and Storage.”
The goal of this research is to cut the total energy cost that is needed to achieve near-Shannon capacity information transmission and storage. The proposed research addresses the frontiers of error-correction coding (ECC) and very-large-scale integration (VLSI) by advancing low-energy coding algorithms and algorithm-oriented circuit techniques.
While it is common to use channel coding to save transmit energy for a reliable delivery, the decode energy of some of the best capacity-approaching codes can be prohibitive due to VLSI circuit complexities and overtake transmit energy. Many capacity-approaching codes are not guaranteed to work well either, as they often give up their effectiveness at low error rates, requiring extra transmit energy to maintain their performance.
This project aims to stem the rising energy cost for both transmit and decode, which poses obstacles to future high-performance applications, such as optical and wireline communications. Even more severe impediments are placed on low-energy applications, such as battery-powered portable devices and sensors, in their path of acquiring more robust communication and storage capabilities.
This research will advance state-of-the-art coding algorithms and techniques by addressing two research frontiers: (1) the intrinsic weakness of some high-performance channel codes that is manifested as error floors; and (2) the high decode energy due to interconnection complexity and memory inefficiency.
Students will be trained in both coding theory and integrated circuits through the course of the project, which will draw a broad participation of students, professionals, and industrial partners in collaborative research and education.
Prof. Zhang’s research interests include VLSI architecture, digital systems, and implementations of communication and signal processing systems. Specifically, he is investigating energy-efficient communications and signal processing system design that spans algorithm design and analysis, architectural optimizaiton, and efficient hardware implementation. He has taught the junior level undergraduate course, Digital Integrated Circuits, and and senior level undergraduate and graduate-level course VLSI Design I. In addition, he is planning a special course on VLSI digital signal processing systems.
The CAREER grant is one of NSF’s most prestigious awards, conferred for “the early career-development activities of those teacher-scholars who most effectively integrate research and education within the context of the mission of their organization.”