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Waste Factor: A New Metric for Evaluating Power Efficiency in any Cascade

Signal Processing 2024-02-05 v3

Abstract

In this paper, we expand upon a new metric called the Waste Factor (WW), a mathematical framework used to evaluate power efficiency in cascaded communication systems, by accounting for power wasted in individual components along a cascade. We show that the derivation of the Waste Factor, a unifying metric for defining wasted power along the signal path of any cascade, is similar to the mathematical approach used by H. Friis in 1944 to develop the Noise Factor (FF), which has since served as a unifying metric for quantifying additive noise power in a cascade. Furthermore, the mathematical formulation of WW can be utilized in artificial intelligence (AI) and machine learning (ML) design and control for enhanced power efficiency. We consider the power usage effectiveness (PUE), which is a widely used energy efficiency metric for data centers, to evaluate WW for the data center as a whole. The use of WW allows easy comparison of power efficiency between data centers and their components. Our study further explores how insertion loss of components in a cascaded communication system influences WW at 28 GHz and 142 GHz along with the data rate performance, evaluated using the consumption efficiency factor (CEF). We observe CEF's marked sensitivity, particularly to phase shifter insertion loss changes. Notably, CEF variations are more prominent in uplink transmissions, whereas downlink transmissions offer relative CEF stability. Our exploration also covers the effects of varying User Equipment (UE) and Base Station (BS) deployment density on CEF in cellular networks. This work underscores the enhanced energy efficiency at 142 GHz, compared to 28 GHz, as UE and BS numbers escalate.

Keywords

Cite

@article{arxiv.2309.01018,
  title  = {Waste Factor: A New Metric for Evaluating Power Efficiency in any Cascade},
  author = {Mingjun Ying and Dipankar Shakya and Hitesh Poddar and Theodore S. Rappaport},
  journal= {arXiv preprint arXiv:2309.01018},
  year   = {2024}
}

Comments

6 pages, 3 figures, 2023 IEEE Global Communications Conference

R2 v1 2026-06-28T12:11:14.402Z