Green Codes: Energy-Efficient Short-Range Communication

TL;DR

This paper introduces a new framework for designing energy-efficient communication codes that account for both transmission and processing energy, showing that optimal rates are bounded away from zero and approach one as error probability decreases.

Contribution

It develops a model incorporating processing energy into the design of green codes and derives bounds showing the optimal rate is bounded away from zero, contrary to classical theory.

Findings

Optimal rate for green codes is bounded away from zero.

As error probability decreases, the optimal rate approaches one.

Processing energy significantly influences the design of energy-efficient codes.

Abstract

A green code attempts to minimize the total energy per-bit required to communicate across a noisy channel. The classical information-theoretic approach neglects the energy expended in processing the data at the encoder and the decoder and only minimizes the energy required for transmissions. Since there is no cost associated with using more degrees of freedom, the traditionally optimal strategy is to communicate at rate zero. In this work, we use our recently proposed model for the power consumed by iterative message passing. Using generalized sphere-packing bounds on the decoding power, we find lower bounds on the total energy consumed in the transmissions and the decoding, allowing for freedom in the choice of the rate. We show that contrary to the classical intuition, the rate for green codes is bounded away from zero for any given error probability. In fact, as the desired bit-error probability goes to zero, the optimizing rate for our bounds converges to 1.