Effect of Inter-Cell Inter-Radio Access Technology (RAT) interference on the performance of multi-RAT cellular systems
Bibliographic record
Abstract
Containing interference within cellular communication systems requires the use of dedicated frequency bands to mitigate interference from other wireless systems. Based on this design principle, the Radio Frequency (RF) resources of a multi-Radio Access Technology (RAT) cellular system are apportioned between co-deployed RATs. However, traffic variations within multi-RAT systems result in the suboptimal utilization of RF resources under fixed, system-level spectrum allocation policies. On the other hand, flexible spectrum allocation policies that permit using the same frequency band to deploy different RATs at different locations introduce Inter-cell inter-RAT Interference (IRI). The potential impact of IRI prevents the use of flexible spectrum management techniques that disrupt system-level spectrum allocation in multi-RAT systems. This paper studies the effect of IRI on the performance of multi-RAT cellular systems employing Global System for Mobile Communications (GSM), High Speed Packet Access (HSPA) and Long Term Evolution (LTE). Detailed system level simulations are performed to measure the impact of deploying different RATs at different locations using the same frequency band.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".