Speculative Energy Scheduling for LDPC Decoding

Weihuang Wang and Gwan Choi
Texas A&M University


This paper presents a low-power LDPC decoder design based on speculative scheduling of energy necessary to decode dynamically varying data frame in fading channels. The proposed scheme pre-analyzes each received data frame to estimate the maximum number of necessary iterations for frame convergence. The results are then used to dynamically adjust decoder frequency and switch between multiple-voltage levels; thereby energy use is minimized. This is in contrast to the conventional fixed-iteration decoding schemes that operates at a fixed voltage level regardless the quality of data received. The result is a decoder implementation that provides a judicious trade-off between power consumption and coding gain.