CAREER: Removing Energy Barrier Towards Capacity-Approaching Information Transmission and Storage

Regents Of The University Of Michigan - Ann Arbor, Ann Arbor MI

Investigators

Abstract

Project Abstract Removing Energy Barrier towards Capacity-Approaching Information Transmission and Storage The objective of this research is to cut the total energy of achieving near Shannon capacity information transmission and storage. 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 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. The rising energy for both transmit and decode poses obstacles to future high-performance applications, such as optical and wireline communications, due to the escalating cost of operating closer to the ultimate channel capacity. 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 advances state-of-the-art coding algorithms and techniques by addressing two research frontiers of near-capacity low-density parity-check (LDPC) codes: (1) the intrinsic weakness of LDPC codes that is manifested as error floors; and (2) the high decode energy due to interconnection complexity and memory inefficiency. The approaches span coding theory and integrated circuits, and their novelties are threefold: (1) creation of a universal, low-cost local search algorithm to overcome error floors; (2) creation of transient memory to exploit data access pattern for low energy; and (3) new techniques to improve the achievable performance of non-binary LDPC codes while reducing interconnection complexity. This project trains students in both coding theory and integrated circuits and draws broad participation of students, professional colleagues, and industrial partners in collaborative research and education.