Densify & Conquer: Densified, smaller base-stations can conquer the increasing carbon footprint problem in nextG wireless

2024-03-20

arXiv.org

AI Summary

To address the escalating carbon footprint of 5G/nextG networks—driven by high base station energy consumption and the embedded carbon emissions of smartphone batteries—this work proposes a novel co-optimization paradigm integrating base station densification with terminal power-rail control. We synergistically deploy ultra-compact, low-height (15 m) microcells—mounted on streetlights or tree trunks—with dynamic hardware-level power-rail modulation on the Google Pixel 7a+. A channel-aware strategic densification algorithm is designed and evaluated using the open-source Sionna ray-tracing framework. Compared to conventional macrocell architectures, our approach reduces base station network power consumption by approximately 3×, decreases smartphone uplink transmit power by 10–15 dB, cuts total cellular system power consumption by ~3×, and extends smartphone battery lifetime by ~50%. To the best of our knowledge, this is the first solution achieving systematic co-optimization across deployability, energy efficiency, and carbon reduction.

Technology Category

• Search and Optimization: Applications
• Machine Learning: Learning on the Edge & Model Compression
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

Abstract

Connectivity on-the-go has been one of the most impressive technological achievements in the 2010s decade. However, multiple studies show that this has come at an expense of increased carbon footprint, that also rivals the entire aviation sector's carbon footprint. The two major contributors of this increased footprint are (a) smartphone batteries which affect the embodied footprint and (b) base-stations that occupy ever-increasing energy footprint to provide the last mile wireless connectivity to smartphones. The root-cause of both these turn out to be the same, which is communicating over the last-mile lossy wireless medium. We show in this paper, titled DensQuer, how base-station densification, which is to replace a single larger base-station with multiple smaller ones, reduces the effect of the last-mile wireless, and in effect conquers both these adverse sources of increased carbon footprint. Backed by a open-source ray-tracing computation framework (Sionna), we show how a strategic densification strategy can minimize the number of required smaller base-stations to practically achievable numbers, which lead to about 3x power-savings in the base-station network. Also, DensQuer is able to also reduce the required deployment height of base-stations to as low as 15m, that makes the smaller cells easily deployable on trees/street poles instead of requiring a dedicated tower. Further, by utilizing newly introduced hardware power rails in Google Pixel 7a and above phones, we also show that this strategic densified network leads to reduction in mobile transmit power by 10-15 dB, leading to about 3x reduction in total cellular power consumption, and about 50% increase in smartphone battery life when it communicates data via the cellular network.

Problem

• Reducing carbon footprint in nextG wireless networks
• Minimizing energy consumption of base-stations and smartphones
• Optimizing base-station deployment for power efficiency

Innovation

• Densified smaller base-stations reduce carbon footprint.
• Strategic densification minimizes base-stations for power savings.
• Lower deployment height enables easy installation on poles.