Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 495

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Energy-Efficient Base-Stations Sleep-Mode Techniques in Green Cellular Networks: A Survey

Open access
Wu, Jingjin, Zhang, Yujing, Zukerman, Moshe, Yung, Edward Kai-Ning·2015·IEEE Communications Surveys & Tutorials

Abstract

Due to global climate change as well as economic concern of network operators, energy consumption of the infrastructure of cellular networks, or “Green Cellular Networking,” has become a popular research topic. While energy saving can be achieved by adopting renewable energy resources or improving design of certain hardware (e.g., power amplifier) to make it more energy-efficient, the cost of purchasing, replacing, and installing new equipment (including manpower, transportation, disruption to normal operation, as well as associated energy and direct cost) is often prohibitive. By comparison, approaches that work on the operating protocols of the system do not require changes to current network architecture, making them far less costly and easier for testing and implementation. In this survey, we first present facts and figures that highlight the importance of green mobile networking and then review existing green cellular networking research with particular focus on techniques that incorporate the concept of the “sleep mode” in base stations. It takes advantage of changing traffic patterns on daily or weekly basis and selectively switches some lightly loaded base stations to low energy consumption modes. As base stations are responsible for the large amount of energy consumed in cellular networks, these approaches have the potential to save a significant amount of energy, as shown in various studies. However, it is noticed that certain simplifying assumptions made in the published papers introduce inaccuracies. This review will discuss these assumptions, particularly, an assumption that ignores the effect of traffic-load-dependent factors on energy consumption. We show here that considering this effect may lead to noticeably lower benefit than in models that ignore this effect. Finally, potential future research directions are discussed.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1109/comst.2015.2403395

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 2 references

Cited by

See all 495

Metadata

Authors
Wu, J., Zhang, Y., Zukerman, M., & Yung, E. K.-N.
Venue
IEEE Communications Surveys & Tutorials
Published
2015
Volume
17
Issue
2
Pages
803-826
ISSN
  • 1553-877X (ISSN-L)
  • 2373-745X
OpenAlex
W1991898587
Cited by
495
References
2
FWCI
28.71
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Energy-Efficient Base-Stations Sleep-Mode Techniques in Green Cellular Networks: A Survey. https://app.cochat.ai/papers/10.1109/comst.2015.2403395
The paper
Wu, J., Zhang, Y., Zukerman, M., & Yung, E. K.-N. (2015). Energy-Efficient Base-Stations Sleep-Mode Techniques in Green Cellular Networks: A Survey. IEEE Communications Surveys & Tutorials. https://doi.org/10.1109/comst.2015.2403395

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.