5G DIY: Impact of Different Elements on the Performance of an E2E 5G Standalone Testbed
Why this work is in the frame
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Bibliographic record
Abstract
5G, the fifth generation of mobile networks, promises new services, faster speeds, lower latency, and increased network capacity. A 5G network has three main elements: the Radio Access Network (RAN) which can be further divided into a hardware component, called software-defined radio (SDR), a software component, the core network and the User Equipment (UE). Recent years have seen the emergence of an “open” paradigm where the different elements of a 5G network are designed by different developers, and as a result can be separately modified and then integrated to enhance network functionality. This paper presents a framework to compare the impact of different elements on the performance of an end-to-end 5G standalone testbed. In particular, using open5GS as the core and 5G modems as the UE(s), we compare the performance of the recently released “O-RAN native suite, srsRAN-Project” to its srsRAN predecessor for two different SDRs (Ettus USRPs B210 and X410), over wireless and wired channels, in a single cell with one or two UEs. It is concluded that srsRAN-Project, with X410 as the SDR, provides the most stable and consistent performance over wired and wireless channels in both single-UE as well as multi-UE testbeds.
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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 | 0.000 |
| 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 it