Secondary User Access in LTE Architecture Based on a Base-Station-Centric Framework With Dynamic Pricing
Bibliographic record
Abstract
Dynamic spectrum access (DSA) techniques based on the exclusive-use model provide a huge opportunity for wireless service providers (WSPs) to improve the spectrum utilization in their licensed bands and generate additional profits by allowing temporary wireless access to unsubscribed secondary users (SUs). This paper presents a techno-economic analysis for regulated SU access based on a novel base station (BS)-centric framework, where SUs coexist with the subscribers, i.e., primary users (PUs), on a mutually exclusive basis. Considering the highly competitive WSP environment, the proposed framework is aimed at maximizing the localized spectrum utilization within the static spectrum licensed to the WSP and assumes no cooperation and no spectrum sharing among WSPs, thus making this a business case for implementation. The dynamic incentive-based SU pricing model proposed in this paper has the inherent capability of call admission control and, hence, is useful in attracting SUs to obtain temporary wireless access during periods of low PU demand, thus improving spectrum usage in the temporal domain. Although SU access is regulated by the WSP at their BS, the SUs have the freedom to connect or handoff to their preferred BS in the area based on the SU price quoted by the WSP. The implementation of the proposed framework to Long Term Evolution (LTE) infrastructure requires minimal enhancements and can be potentially attractive to WSPs, since the SU devices in this framework do not require spectrum sensing cognitive capabilities. Considering all the aforementioned aspects, this paper can be considered an intermediate step in the evolution toward complete DSA.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".