Waste Factor and Waste Figure: A Unified Theory for Modeling and Analyzing Wasted Power in Radio Access Networks for Improved Sustainability

TL;DR

The paper introduces Waste Factor ($W$) as a unified, cascade-and-parallel metric for energy efficiency in wireless networks, addressing the limitations of conventional EE metrics in RANs. It develops a rigorous theory to compute $W$ across cascaded components and parallel MISO/SIMO/MIMO configurations, linking wasted power to signal output via $W = P_{\text{consumed,path}}/P_{\text{signal}}$ and $P_{\text{wasted}} = (W-1)P_{\text{signal}}$. The authors apply the framework to passive and active RAN components, the wireless channel, and distributed MU-MIMO scenarios, providing closed-form expressions and measurement-based approaches. Simulation results at 3.5/17/28 GHz show that increasing base-station density and higher carrier frequencies can reduce $W$ and overall power waste, highlighting potential pathways toward greener 5G/6G networks. The work argues that $W$ offers deeper, traffic-load-independent insights into energy efficiency than standard EE metrics, enabling more informed planning, optimization, and real-time management of next-generation wireless systems.

Abstract

This paper introduces Waste Factor (W), also denoted as Waste Figure (WF) in dB, a promising new metric for quantifying energy efficiency in a wide range of circuits and systems applications, including data centers and RANs. Also, the networks used to connect data centers and AI computing engines with users for ML applications must become more power efficient. This paper illustrates the limitations of existing energy efficiency metrics that inadequately capture the intricate energy dynamics of RAN components. We delineate the methodology for applying W across various network configurations, including MISO, SIMO, and MIMO systems, and demonstrate the effectiveness of W in identifying energy optimization opportunities. Our findings reveal that W not only offers nuanced insights into the energy performance of RANs but also facilitates informed decision-making for network design and operational efficiency. Furthermore, we show how W can be integrated with other KPIs to guide the development of optimal strategies for enhancing network energy efficiency under different operational conditions. Additionally, we present simulation results for a distributed multi-user MIMO system at 3.5, 17, and 28 GHz, demonstrating overall network power efficiency on a per square kilometer basis, and show how overall W decreases with an increasing number of base stations and increasing carrier frequency. This paper shows that adopting W as a figure of merit can significantly contribute to the sustainability and energy optimization of next-generation wireless communication networks, paving the way for greener and more sustainable, energy-efficient 5G and 6G technologies.

Figures (21)

• Figure 1: Energy consumption distribution in telecommunication operators gsma2024going.
• Figure 2: A general cascaded communication system composed of two devices, and components not on the signal path are deemed to consume $P_{non-path}$ power.
• Figure 3: A two TX and one RX MISO communication system.
• Figure 4: A MISO system with M paralleled input cascade.
• Figure 5: A SIMO system with M paralleled output cascade.