Energy efficient MIMO processing: A case study of opportunistic run-time approximations

Abstract

Worst-case design is one of the keys to practical engineering: create solutions that can withstand the most adverse possible conditions. Yet, the ever-growing need for higher energy efficiency suggest a grim outlook for worst-case design in the future. In this paper, we propose opportunistic runtime approximations to enable a continuous adaptation of the processing precision (operator type and bitwidth) to the actual execution context without modifying the algorithm functionality. We show that by relaxing the processing precision whenever possible, a VLSI implementation of an advanced wireless receiver algorithm based on opportunistic run-time approximations can save about 40% of the energy consumed by an optimized static implementation. These energy savings are achieved at the expense of a slight increase in overall chip area.