Long-Term Techno-Economic Analysis of Sustainable and Zero Grid Cellular Base Station
Bibliographic record
Abstract
Green wireless networking has attracted considerable research attention, especially in academics and industry from economic and ecological perspectives. Promoting wireless infrastructures by exploiting green power sources has the potential to enhance sustainability and address the adverse impact of conventional power sources. A sustainable optimal standalone solar-powered model for green cellular base stations in urban locations of South Korea is proposed in this work to extend 24-hour uninterrupted power supply support to LTE cellular base stations (BSs) and take advantage of integrated storage devices. The optimal system architecture, energy management, and economic analysis are examined using the hybrid optimization model for electric renewable optimization software based on actual prevailing conditions of regions and their technical feasibility. Results showed that the proposed solar photovoltaic system can achieve significant operational expenditure savings of up to 43% and 43.58% in on- and off-grid sites, respectively, and reduce greenhouse gas emissions in the telecommunications sector. Moreover, the results of this study can provide a stronger platform for a sustainable green wireless network paradigm that can ensure energy sustainability compared with conventional technology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".