Wi-Fi Coverage Calculator
The formula
What the wi-fi cell radius tells you
How far an AP reaches at your chosen edge signal, with real indoor wall losses per band — the planning number behind "how many APs do I need".
Calculation: Budget = EIRP − edge RSSI − walls×per-band loss; radius from 20log d + 20log f − 27.55 = path loss. Enter your inputs and every substitution is shown below the result.
Reading the result
Edge RSSI −67 dBm supports ~100 Mbps MCS; drop to −75 and you bought coverage nobody can use. Design for the data rate, not for the bars.
Rules of thumb: Typical office: 2.4 GHz reaches ~25 m through 2 walls, 5 GHz ~16 m, 6 GHz ~12 m at a −67 dBm edge.
Limitations and best practice
Transmit power is capped per country (100 mP EIRP most places) — the real lever is the client uplink, and 6 GHz dies first on the return path.
This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Frequently asked questions
Should I just crank the power?
Does this match the vendor heat-map tool?
Source & methodology
Indoor propagation from ITU-R P.1238 attenuation guidance; per-band wall-loss figures from Wi-Fi Alliance planning notes.
Wi-Fi Coverage: what this tool answers
Time is the one input nobody can renegotiate, which makes getting the arithmetic right worth the minute it takes. There are plenty of pages about Wi-Fi Coverage; almost none of them show the working. This one does: the formula, every input, a fully computed example, and a sensitivity analysis calculated live from this engine’s own defaults.
A calculation like this one is worth roughly as much as a careful sentence: it forces several vague considerations into one comparable quantity. Once Wi-Fi Coverage is on the table, the argument can stop being about impressions.
The number itself is the easy part. What takes judgement is knowing which inputs are facts in your situation and which are guesses wearing a decimal point — a distinction this page makes explicit for every field above.
What makes a calculation page trustworthy is that its copy is derived from its own arithmetic: here design radius after walls = 17.3 m, recomputed every time a field changes, and the sensitivity section ranks the inputs that move the result — Design edge RSSI first, at ≈116.3 % of the headline for a ten-percent error either way in that input. Read the sections in order and you will be able to reproduce every figure by hand.
The Wi-Fi Coverage formula, explained
Here is the complete model this tool runs — Budget = EIRP − edge RSSI − walls×per-band loss; radius from 20log d + 20log f − 27.55 = path loss — with each input explained below. If a competitor’s page gives you a different answer from the same inputs, this is the text that settles which of you is right.
AP EIRP (dBm) (example value 19) is a numeric input whose unit is fixed by the label; a wrong unit is a wrong answer wearing a plausible disguise. This input feeds the formula directly; a defensible figure here is worth more than false precision anywhere else.
Band (example value 5 GHz) is a selector, not a measurement: the engine follows a different route for each option. This input feeds the formula directly; a defensible figure here is worth more than false precision anywhere else.
Design edge RSSI (dBm) (example value -67) is a measured number in the unit named by the label; the formula does not convert for you. If you are unsure what belongs in this field, look at the printed steps: the substitution shows exactly how the engine uses it.
Interior walls to the edge (example value 2) is a measured number in the unit named by the label; the formula does not convert for you. The example value is there to demonstrate the mechanics, not to describe your situation — overwrite it.
What each “Band” choice actually does: 2.4 GHz → 61.7 m · 5 GHz → 17.3 m · 6 GHz → 9.8 m These figures are computed from this engine, not estimated — switch the dropdown above and you will land on exactly these numbers.
Wi-Fi Coverage with real numbers, step by step
The tool prints its own working; this is the same arithmetic on the example values, reproduced so you can follow it by hand. Starting figures: AP EIRP (dBm), Band, Design edge RSSI (dBm), Interior walls to the edge. The endpoint of that chain is 17.3 m of design radius after walls, sitting in the “Normal indoor cell” band.
- Budget = 19 − (-67) = 86 dB, minus 2 walls × 7 dB
- Path-loss allowance = 72.0 dB
- Invert FSPL at 5,500 MHz ⇒ d = 17.3 m
- Cell area ≈ πr² × 0.6 non-circular factor = 562 m²
Usable coverage area — 562 m². Compare it against the main result of 17.3 m before drawing conclusions.
APs for a 300 m² floor — 1. Compare it against the main result of 17.3 m before drawing conclusions.
2.4 GHz radius, same wall count — 61.7 m. This is the number experienced users quote when the headline alone would mislead.
Link budget consumed by walls — 14.0 dB. This is the number experienced users quote when the headline alone would mislead.
Keep this worked example open while you enter your own figures: matching the shape of the substitution is the fastest way to spot a unit or convention mistake.
The Wi-Fi Coverage corridor: your result across a realistic band
The honest version of any estimate is a corridor, and this one is cheap to produce: Wi-Fi Coverage was recomputed at 5 points along the dominant input, with every other field left untouched.
| Design edge RSSI setting | Design radius after walls |
|---|---|
| 80 % of the example value | 3.7 m |
| 90 % of the example value | 8.0 m |
| example inputs | 17.3 m |
| 110 % of the example value | 37.3 m |
| 120 % of the example value | 80.7 m |
That spread — 3.7 m at the low end, 80.7 m at the high — is what a careful read of Wi-Fi Coverage looks like: a band you can state out loud, with the reason for each edge. Reproduce it in the form above by editing Design edge RSSI alone; the substitution steps will follow your figures exactly.
Sensitivity: which inputs change Wi-Fi Coverage the most
Nobody should have to guess which input matters. The engine was re-run once per field below — ten percent up, ten percent down, everything else frozen — and the results ranked by how far they moved the design radius after walls. It is the fastest honest answer to “what matters most in Wi-Fi Coverage?” — and it is specific to these defaults, because sensitivity moves with the starting point.
- Design edge RSSI +10 % → Wi-Fi Coverage = 37.3 m · −10 % → 8.0 m (the design radius after walls shifts ≈116.3 %)
- AP EIRP: ten percent up gives 21.5 m, ten percent down gives 13.9 m — ≈24.5 % of the design radius after walls either way
- Interior walls to the edge: ten percent up gives 14.7 m, ten percent down gives 20.3 m — ≈17.5 % of the design radius after walls either way
Design edge RSSI is the dominant lever here: ten percent either way moves the result by about 116.3 %, from 8.0 m to 37.3 m. That is where a careless figure does the most damage, so check it against a source, and treat AP EIRP as the second priority (≈24.5 % per ten percent). The rest of the inputs earn only a rounding-error of attention, and that asymmetry is the practical payoff of measuring rather than asserting.
What a Wi-Fi Coverage of 17.3 m means in practice
Nobody acts on a bare figure — they act on a figure with a comparison attached. On the example inputs the band reads “Normal indoor cell”; your own figures place you on a different rung of the same ladder. The sensitivity list shows how far a modest input error moves you along that ladder: for Design edge RSSI, ±10 % covers 8.0 m to 37.3 m. The practical reading rules: compare against your own history before comparing against other people; treat band boundaries as zones, not walls — one point on the wrong side of a threshold rarely changes a real outcome; and when a companion output contradicts the headline, believe the pair.
Set Wi-Fi Coverage beside its neighbours and it usually plays a specific role: this figure establishes the size of something, and the neighbouring tools establish whether that size is acceptable. Skipping the first step makes the second one arbitrary.
How people get Wi-Fi Coverage wrong
Transmit power is capped per country (100 mP EIRP most places) — the real lever is the client uplink, and 6 GHz dies first on the return path. This calculator gives an estimate based on standard formulas; it is not professional financial, medical, legal or engineering advice. Verify anything you plan to act on with a qualified professional and your own records.
Reusing a Wi-Fi Coverage from last season. In Technology & Computing the inputs are the thing that drifts; the formula does not.
One mistake is specific to this engine: assuming every input matters equally. The computation above shows Design edge RSSI dominating — a careful figure there beats false precision everywhere else.
The subtlest error is answering the wrong question precisely. Confirm that design radius after walls is actually the quantity your decision needs — the arithmetic is flawless either way, which is what makes the mistake invisible.
Before you trust your Wi-Fi Coverage: a short checklist
- Check that every field the formula needs actually arrived from a document, not from recollection.
- Record the date and the inputs alongside the number so future-you knows what was assumed.
- Re-verify Design edge RSSI against a source document — ten percent of error there moves the headline by ≈116.3 %.
- Compare the result with one independent method or published benchmark.
- Confirm the example values are plausible for your own situation before replacing them.
- Run the ±10 % stress on the top two levers and check that your conclusion survives both.
A routine for decision-grade Wi-Fi Coverage
The tool does the arithmetic; the routine below is what makes the arithmetic trustworthy. Five steps, a minute total — and afterwards you will know not just what the number is, but which assumption produced it.
Step 1 — gather before you type. Wi-Fi Coverage depends on ap eirp (dbm), band, design edge rssi (dbm), interior walls to the edge. Collect them from a source document — a statement, a report, an invoice, a log — rather than from memory, because recalled inputs are the single largest cause of wrong results. The point of transparency is that a reader can disagree with a specific line rather than with you.
Step 2 — compute the version you would not be embarrassed by. If a stranger audited your inputs, which set would you hand over? Enter that set, read the result, and treat everything else as upside. Say the answer out loud before you save it; if it sounds wrong, the model did not change, your understanding did.
Step 3 — measure what deserves measuring. The ranked levers above tell you where a careful figure pays off. Everything else can stay approximate, which is a licence to stop hunting for data you do not need. Most surprises in numbers are surprises about inputs, not about formulas.
Step 4 — run the scenario trio. Expected, pessimistic, optimistic. The gap between pessimistic and expected is the number to plan against; the optimistic result is useful only as a ceiling. Repeating a calculation with the same numbers proves only that the arithmetic is reliable — which is worth knowing.
Step 5 — write the one-line memo. “Design radius after walls = 17.3 m on this date, from these inputs.” That line is the entire deliverable; everything else on this page is how you earned the right to write it. Compare the calculation to the rough guess you arrived with, and ask why they differ.
The real-world conversations Wi-Fi Coverage settles
In Networks & Storage the figure computed here is usually the first one somebody asks to see. Having it — with the formula behind it — changes your position in the conversation from participant to reference. The fastest sanity test is to guess the answer first and see how far the calculation disagrees.
The audience for this page is people planning around a point or span in time. In professional Networks & Storage practice the pattern is always the same — screen with Wi-Fi Coverage, then invest slow analysis only in whatever survives the screen. A figure with a date beside it becomes evidence; without one it stays an anecdote.
Treat Wi-Fi Coverage like a smoke alarm rather than a painting — its value is in being tested periodically, not in being admired once. If the verdict changes with a ten-percent nudge, report the nudge alongside the number.
Wi-Fi Coverage — frequently asked questions
What affects Wi-Fi Coverage the most?
The short answer: Design edge RSSI. The longer answer is the sensitivity table on this page, where every numeric input was probed by ten percent and the design radius after walls recalculated — Design edge RSSI moved it furthest, by roughly 116.3 % (8.0 m to 37.3 m).
Which matters more: ap eirp or design edge rssi?
For Wi-Fi Coverage, Design edge RSSI wins the head-to-head (≈116.3 % against ≈24.5 % per ten-percent change). Knowing which input dominates is the difference between careful work and merely slow work.
How much does the “Band” choice change the answer?
A great deal, on these inputs: Wi-Fi Coverage comes out at 9.8 m on the lowest option (“6 GHz”) and 61.7 m on the highest (“2.4 GHz”). Each option is listed with its computed value so you can see what the choice is worth before you make it.
What is a typical Wi-Fi Coverage?
There is no honest universal average for Wi-Fi Coverage, but there is a reference point: the defaults on this page produce 17.3 m (Normal indoor cell). Replace the inputs with your own and compare — that comparison is the useful meaning of “typical”.
How do I calculate Wi-Fi Coverage by hand?
Use the stated model — Budget = EIRP − edge RSSI − walls×per-band loss; radius from 20log d + 20log f − 27.55 = path loss — and substitute in the order the tool prints (it starts from Budget = 19 − (-67) = 86 dB, minus 2 walls × 7 dB). On the example inputs the hand route lands on 17.3 m, exactly what the calculator shows. A spreadsheet reproduces it in two or three cells; doing it once by hand is what makes the automated answer trustworthy.
What happens to Wi-Fi Coverage if design edge rssi changes by 10 %?
The engine was re-run with that field moved by ten percent while everything else stayed fixed: the design radius after walls goes across 8.0 m to 37.3 m, a swing of roughly 116.3 % around the 17.3 m baseline. That ratio is the practical definition of how much this input matters.
Is the Wi-Fi Coverage result of 17.3 m good or bad?
The tool answers “what”, not “whether”: 17.3 m carries the verdict “Normal indoor cell” for the default case, which is a starting interpretation rather than a verdict on your situation. Re-run with your own figures and compare the bands.
How do I calculate Wi-Fi Coverage manually?
Write down the inputs, then follow the printed steps in order — Budget = EIRP − edge RSSI − walls×per-band loss; radius from 20log d + 20log f − 27.55 = path loss. A spreadsheet replicates it with two or three cells. The manual route is worth doing once to build intuition; after that the calculator saves time and eliminates transcription slips.
What affects Wi-Fi Coverage the most?
Sensitivity depends on where you start, but the inputs AP EIRP (dBm) and Band typically move Wi-Fi Coverage further than the rest because they enter the formula multiplicatively. If you can only measure two things well, measure those and hold the others at conservative defaults.
Should I just crank the power?
Both directions matter: a shouting AP with a whispering laptop still fails. Lower power with more APs is the roaming-friendly answer.
Does this match the vendor heat-map tool?
Same physics minus your specific drywall; validate with an on-site predictive or proactive survey before buying 20 units.
Can this tool see the numbers I type?
It cannot. There is no submission step: the calculation happens in your browser and the result disappears when you close the page. Treat the fields above as a scratchpad rather than a form.
Key terms on this page
- Usable coverage area
- 562 m² on the example inputs — a companion figure printed beside the headline of Wi-Fi Coverage so that no result is read in isolation.
- APs for a 300 m² floor
- 1 on the example inputs — a companion figure printed beside the headline of Wi-Fi Coverage so that no result is read in isolation.
- 2.4 GHz radius, same wall count
- 61.7 m on the example inputs — a companion figure printed beside the headline of Wi-Fi Coverage so that no result is read in isolation.
- Design radius after walls
- The primary output of this tool: 17.3 m for the default inputs, computed exactly from Budget = EIRP − edge RSSI − walls×per-band loss; radius from 20log d + 20log f − 27.55 = path loss.
- Worked example
- The step-by-step substitution printed above, so the arithmetic can be re-derived by hand or in a spreadsheet.
- Verdict band
- The plain-language label — here “Normal indoor cell” — mapping the computed figure onto experience-based ranges for Technology & Computing.
- Sensitivity (±10 %)
- How far the Wi-Fi Coverage moves when a single input is nudged ten percent either way; the ranked list on this page is computed live from this engine.
The provenance of this Wi-Fi Coverage calculation
There is no black box on this page — the engine evaluates Budget = EIRP − edge RSSI − walls×per-band loss; radius from 20log d + 20log f − 27.55 = path loss. Source of record: Indoor propagation from ITU-R P.1238 attenuation guidance; per-band wall-loss figures from Wi-Fi Alliance planning notes. Specialist software layers extra coefficients on top of the same algebra; none are hidden here, and that transparency is what makes a disagreement traceable to a specific input instead of a black box.
Treat the output as a precise answer to the question you typed: exact arithmetic, transparent formula, published source, no hidden rounding. The sensitivity table above is part of that promise rather than a bonus: it lets you see how much of the result depends on how carefully you measured.
Next steps after the calculation
Re-run whenever a start date moves — time calculations compound small shifts into large misses.
The audience here is people planning around a point or span in time. Everything you need to defend the result — formula, substitution, sensitivity, source — is printed above, so the only remaining variable is the honesty of your inputs.