5G NR Network Planning Analysis using 700 Mhz and 2.3 Ghz Frequency in The Jababeka Industrial Area
Bibliographic record
Abstract
This research designed a 5G NR network using 700 MHz and 2.3 GHz frequencies with 30 MHz bandwidth in the Jababeka industrial area covering an area of 5600 hectares. The Propagation Model used by Urban Macrocell (UMa) in non line of sight (NLOS) conditions according to 3GPP TR 38901 standard with Synchronization signal-reference signal received power (SS-RSRP) and Synchronization Signal to Interference and Noise Ratio (SS-SINR) parameters. Coverage prediction simulation using Atoll 3.4 consists of 4 scenarios. Scenario 1 uses a frequency of 2.3 GHz downlink, scenario 2 uses a frequency of 2.3 GHz uplink, scenario 3 uses a frequency of 700 MHz downlink and scenario 4 uses a frequency of 700 MHz uplink. Parameters analyzed were signal strength (SS-RSRP > -110 dBm) and signal quality (SS-SINR > 5 dB). The simulation results of scenario 1 get a signal strength of 61% and signal quality of 73.71% from the Jababeka area. Scenario 2 gets 100% for signal strength and 75.35% for signal quality. Scenario 3 gets a signal strength of 72.27% and signal quality of 85.30%. Scenario 4 shows a signal strength of 100% and signal quality of 71.04% from the Jababeka area. Planning with a frequency of 700 MHz shows that the signal strength and signal strength parameters are better than the 2.3 GHz frequency, making it suitable for 5G networks in the Jababeka area. The findings of this study are intended to help Indonesian cellular operators plan and deploy their 5G network.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".