On Complexity, Energy- and Implementation-Efficiency of Channel Decoders

TL;DR

This paper introduces new energy and area efficiency metrics for channel decoders, enabling better benchmarking of implementation efficiency, performance, and flexibility trade-offs in wireless communication systems.

Contribution

It proposes novel efficiency metrics and exploration methodologies that consider data and storage complexity, improving upon traditional operation-counting metrics.

Findings

Energy per decoded bit as an efficiency measure

Throughput per area unit as an implementation metric

Efficiency trajectories for comprehensive benchmarking

Abstract

Future wireless communication systems require efficient and flexible baseband receivers. Meaningful efficiency metrics are key for design space exploration to quantify the algorithmic and the implementation complexity of a receiver. Most of the current established efficiency metrics are based on counting operations, thus neglecting important issues like data and storage complexity. In this paper we introduce suitable energy and area efficiency metrics which resolve the afore-mentioned disadvantages. These are decoded information bit per energy and throughput per area unit. Efficiency metrics are assessed by various implementations of turbo decoders, LDPC decoders and convolutional decoders. New exploration methodologies are presented, which permit an appropriate benchmarking of implementation efficiency, communications performance, and flexibility trade-offs. These exploration methodologies are based on efficiency trajectories rather than a single snapshot metric as done in state-of-the-art approaches.