Energy-Efficient Mobile Communications using an Adaptive Gearbox-PHY under Hardware Constraints

TL;DR

This paper proposes an energy-efficient physical layer architecture called Gearbox-PHY for mobile networks, which adapts modulation schemes to reduce energy consumption, especially at low data rates, considering hardware impairments.

Contribution

It quantifies energy savings of Gearbox-PHY under realistic hardware constraints and demonstrates significant efficiency gains in cellular scenarios.

Findings

Gearbox-PHY achieves up to two orders of magnitude energy savings.

Energy savings are most significant at low data rates.

Hardware impairments like phase noise impact spectral and energy efficiency.

Abstract

Future mobile networks must achieve substantial improvements in energy efficiency to offset the anticipated traffic growth. Despite this requirement, many discussions regarding physical layer design remain primarily focused on peak data rates and spectral efficiency, even though typical network operation is dominated by low-data-rate regimes. To address this mismatch, the Gearbox-PHY was proposed as an energy-efficient physical layer architecture that dynamically switches between modulation schemes and their associated analog front ends in order to adapt to varying operating requirements. This paper quantifies the achievable energy savings by jointly modeling front end power consumption and hardware-aware spectral efficiency to formulate an energy-per-bit minimization problem. To move beyond idealized assumptions, non-ideal hardware effects, including oscillator phase noise and limited quantizer resolution, are incorporated. These impairments simultaneously affect power consumption and achievable spectral efficiency, thereby introducing trade-offs between front end complexity, hardware non-linearities, spectral efficiency, and energy efficiency. Numerical results demonstrate that the Gearbox-PHY enables significant energy savings, particularly at low data rates. Evaluations with spatially distributed users confirm that gains of up to two orders of magnitude persist in a cellular deployment scenario.