| Scenario | f (MHz) | d (km) | hb (m) | hm (m) | Env | Path loss (dB) | Rx power (dBm) |
|---|---|---|---|---|---|---|---|
| Planning baseline | 900 | 5 | 50 | 1.5 | Urban | Calculated on submit | Calculated on submit |
| Same link, suburban | 900 | 5 | 50 | 1.5 | Suburban | Calculated on submit | Calculated on submit |
| Longer reach | 900 | 12 | 70 | 1.5 | Open | Calculated on submit | Calculated on submit |
Click Load Example to populate the form with baseline values.
Urban baseline
f in MHz, d in km, hb and hm in meters. a(hm) depends on city size.
Mobile correction a(hm)
Environment corrections
Link budget
- Enter frequency, distance, and antenna heights in the correct units.
- Choose environment and city size to match your deployment area.
- Add link budget fields to estimate received power and fade margin.
- Use the distance sweep to see how margin changes across coverage.
- Download the CSV or PDF to share results with your team.
Model scope and typical planning ranges
This calculator implements the classic Hata approach for macrocell-style coverage planning. It is commonly applied when frequency is between 150 and 1500 MHz, distance is 1 to 20 km, base antenna height is 30 to 200 m, and mobile height is 1 to 10 m. These ranges keep the logarithmic terms stable and align with field measurements used to shape the original curves.
Environment corrections and expected differences
Urban loss is computed first, then corrected for suburban and open areas. Suburban correction typically reduces loss by a few dB at mid-band values, while open-area correction can reduce loss more strongly as frequency increases. In practice, the difference is visible in your sweep table: open environments generally show higher received power and a larger fade margin at the same distance.
Antenna height leverage in real deployments
Base height influences both the intercept and slope of the distance term through log10(hb). Raising hb usually lowers path loss and softens distance growth, improving coverage robustness. Mobile height affects the a(hm) correction, and small changes near 1 to 2 m can shift predicted loss by multiple dB, especially in dense environments.
Link budget interpretation and decision points
Received power is estimated from transmit power, antenna gains, and all losses including path loss. The calculator also compares received power against a threshold built from sensitivity plus required margin. A positive margin is a simple go/no-go indicator, while a large positive margin supports higher modulation, better reliability, or added penetration losses.
Using the sweep table for coverage boundaries
The sweep feature produces evenly spaced distances and computes path loss, received power, and margin per row. Use it to identify the distance where margin crosses zero and treat that point as a first-order cell edge. For engineering reviews, export the CSV and annotate the rows that represent target service levels and minimum acceptable margin.
Quality checks and practical calibration
Compare predictions against drive-test or site survey results and adjust “misc losses” to represent clutter, building penetration, or seasonal fade. If your spectrum or geometry is outside typical ranges, treat the output as indicative rather than absolute. Consistent parameter sets across scenarios are more valuable than isolated single-point runs.
1) What does the model output represent?
It estimates large-scale median path loss in dB for a macrocell link, then derives received power using your link budget inputs.
2) Should I choose small/medium or large city size?
Select large for dense metropolitan cores with high building density. Use small/medium for typical towns, suburbs, and mixed areas.
3) Why is my margin negative even with high transmit power?
High path loss, excessive losses, or an aggressive required margin can dominate. Check antenna gains, feeder losses, and whether distance is beyond typical limits.
4) How should I set misc losses?
Use misc losses for penetration, clutter, polarization mismatch, and engineering reserve. Start with 0–10 dB, then calibrate against field measurements.
5) Is this suitable for microcells or indoor links?
Not directly. Hata is best for outdoor macro scenarios. For indoor or microcell planning, consider models designed for short distances and heavy clutter.
6) What is the best way to validate results?
Run several scenarios with consistent assumptions, compare against drive-test RSSI/RSRP, and tune losses or margins until predictions align with observed medians.