Low Power Receiver Front Ends: Scaling Laws and Applications

TL;DR

This paper develops theoretical scaling laws linking environment parameters to the power consumption of low-power receiver front ends, providing guidelines for energy-efficient communication system design and adaptive power reduction strategies.

Contribution

It introduces closed-form expressions connecting system parameters with front end power, and analyzes how adaptation can significantly reduce power consumption in communication receivers.

Findings

Power scales at least as SNDR^3/2 under static conditions.

Using coding with moderate gain and simple decoding is most energy-efficient.

Adaptive front ends can reduce power by at least 20x in fluctuating environments.

Abstract

In this paper, we combine communication-theoretic laws with known, practically verified results from circuit theory. As a result, we obtain closed-form theoretical expressions linking fundamental system design and environment parameters with the power consumption of analog front ends for communication receivers. This collection of scaling laws and bounds is meant to serve as a theoretical reference for practical low power front end design. In one set of results, we first find that the front end power consumption scales at least as SNDR^3/2 if environment parameters (fading and blocker levels) are static. The obtained scaling law is subsequently used to derive relations between front end power consumption and several other important communication system parameters, namely, digital modulation constellation size, symbol error probability, error control coding gain and coding rate. Such relations, in turn, can be used when deciding which system design strategies to adopt for low-power applications. For example, if error control coding is employed, the most energy-efficient strategy for the entire receiver is to use codes with moderate coding gain and simple decoding algorithms, such as convolutional codes. In another collection of results, we find how front end power scales with environment parameters if the performance is kept constant. This yields bounds on average power reduction of receivers that adapt to the communication environment. For instance, if a receiver front end adapts to fading fluctuations while keeping the performance above some given minimum requirement, power can theoretically be reduced at least 20x compared to a non-adaptive front end.