Radio Mobile Deluxe is free but not open source radio propagation Windows software that runs on Linux well via WINE.
Installing Radio Mobile Deluxe is straightforward:
Download rmwcore.zip and extract to ~/rmw.
Download English (or other) language code e.g. rmw1166eng.zip and extract to ~/rmw
Install Visual Basic 6 runtime:
Make a script ~/rmw.sh containing
#!/bin/sh
wine ~/rmw/rmweng.exe
Then:
Create a new app icon by creating a file ~/.local/share/applications/rmw.desktop with contents:
#!/usr/bin/env xdg-open
[Desktop Entry]
Type=Application
Exec=wine ~/rmw/rmweng.exe
Name=Radio Mobile Deluxe
Use the Radio Mobile Deluxe menu shortcut or in Terminal
Radio Mobile Deluxe .ant antenna pattern files require Windows/DOS \r\n CRLF line endings even when run under WINE.
Convert Unix LF line ending files with
When using Python to write text files in Linux, by default the line endings will be \n LF line endings.
Force Python to write Windows/DOS CRLF from Linux when using functions with options such as:
numpy.savetxt(newline='\r\n')
That works across operating systems.
Radio Mobile Deluxe through version 11.6 does not reload modified .ant files.
You must close/reopen the entire RMD program to reload a modified antenna pattern file.
err:module:import_dll Library MSVBVM60.DLL (which is needed by L"Z:\rmw\rmweng.exe") not found
Fix:
Alternative open source wireless propagation software:
- Splat RF is also great for radio coverage prediction outdoors.
- PyLayers is for indoor site-specific radio coverage prediction, also suitable for UWB.
This article is about improvised/first check methods to help make “sanity checks” when there is a question if something will work or why it’s not working.
Live streaming with little ability to buffer needs more WiFi signal strength than general Web browsing or little logging sensors.
Normally for good WiFi performance, a starting point is to have at least:
- 20 dB SNR
- -70 dBm RSSI (signal strength)
The signal levels mentioned here are relative and conceptual.
Don’t design according to this highly simplified discussion alone!
A simple SNR estimate can be made by simply looking at desired WiFi signal strength and subtract the next strongest signal on your channel.
For example, your WiFi is -68 dBm and there is another WiFi AP on or overlapping with your channel at -75 dBm, the SNR is no better than -68 - (-75) = 7 dB.
This over-simplified calculation has significant error for RF congested environments, because it does not account for
- non-WiFi interference (microwave overs, baby monitors, Bluetooth, etc.) (makes SNR worse)
- channel occupancy time (is the unwanted co-channel WiFi unused, or are they streaming HD video (heavy utilization) (light usage of unwanted WiFi makes effective SNR better)
Here we assume a worst-case near-far problem, where CSMA/CA isn’t stopping conflicting transmissions because the unit is in the middle between the desired and undesired transmitters that can’t hear each other.
A good 5 GHz AP was tested in an urban environment, with minimal traffic (late at night).
The system configuration was a 40 MHz 5 GHz channel with a few other APs on channel, using Ubiquiti hardware with 20 dBm AP transmit power.
The AP heard phone about 3 dB weaker than phone heard AP.
| RSSI (dBm) |
uplink throughput (Mbps) |
downlink throughput (Mbps) |
| -85 |
5.0 |
30.0 |
| -90 |
4.2 |
7.2 |
| -91 |
3.6 |
4.2 |
A cheap 2.4 GHz AP was tested with minimized environmental variation from outside or inside due to random human activity such as network loading, Bluetooth, microwave ovens, etc.
AP was in adjacent office of commercial building, using a clear channel (no overlap/co-channel in test area), on a holiday (no microwave ovens/bluetooth etc. from employees).
| RSSI (dBm) |
throughput (Mbps) |
MCS / modulation |
streaming video resolution (vertical pixels) |
| -93 - -85 |
0 |
0 / BPSK |
N/A |
| -84 |
0.5 |
2 / QPSK |
144 |
| -83 |
1.3 |
"" |
240 |
| -82 |
1.7 |
"" |
"" |
| -81 |
2.2 |
3 / 16-QAM |
360 |
| -80 |
3.5 |
"" |
"" |
| -79 |
> 4 |
4 / 16-QAM |
480 |
Important factors not considered in this test include: latency, error rate, and increased loading due to transmission repeats.
In many non-interference-free scenarios, streaming video dropouts may occur at these low signal levels.
This is due to people moving about, trees waving, etc. causing signal variability.
Log packet errors, transmission drops and signal levels.
Rather than try to get big antennas for one AP, use multiple APs and allow beamforming to work.
Whenever possible, 5 GHz is much better than 2.4 GHz for most use cases.
Even if you’re at an isolated campground, visitors use WiFi-cellular gateways,
baby monitors, microwave ovens and other 2.4 GHz devices, wiping out your 2.4 GHz premises monitoring system.
It’s important for wireless workers at all levels to remember principles of significant digits, especially when instrument and antenna calibrations have finite accuracies and the need to build in link budget margins to ensure sufficient reliability.
Finer than 0.5 dB precision for field measurements, raises the question of measurement limits.
Even 1-2 dB resolution is hard to achieve in real-world environments.
The table above is generally indicative of trends, but each device has a couple dB ± accuracy between units of the same model, vs. temperature, etc.
Keep in mind always that the environmental variability far dominates the instrument variability.
It’s possible in urban environments on 2.4 GHz to have a -70 dBm signal and 5.5 Mbps raw connection speed.
This is due to high activity on the channel.
A fundamental factor for any radio receiver is the
Johnson-Nyquist thermal noise
floor.
Assuming the system is designed so that the first receiver amplifier (typically called the low noise amplifier or LNA) dominates system performance, we can start with a simple system noise model that assumes a 20 MHz receiver bandwidth at 30 degrees Celsius.
P_noise = kTB
k is Boltzmann Constant, approximated as 1.38 x 10^-23.
T is temperature in Kelvin, here taken as 300K ~ 27°C ~ 80°F.
B is the equivalent receiver bandwidth [Hz].
The decibel expression is much more handy for computing ratios of power, which for convenience is expressed as power relative to one milliwatt “dBm”.
Many times, just to help show that everyone is using the same reference point and units (dBm vs. dBW, say), kTB will be expressed as a constant in dBm with B=1 Hz.
That is, noise power in dBm/Hz.
P_noise,B=1 = 1.38e-23 * 300 = 4.14 zW/Hz
Let’s go from zeptowatts to dBm:
P_noise,B=1 = 10*log10(4.14e-21) + 30 = -173.8 dBm/Hz
where the +30 factor converts from dBW to dBm.
For a 802.11n 20 MHz channel, we can estimate the receiver thermal noise floor power as:
P_noise = -173.8 + 10*log10(20e6) = -100.8 dBm
This means an ideal WiFi 802.11n receiver will have a noise floor of about -101 dBm.
Typical consumer WiFi gear will have a noise figure degrading (raising) this thermal noise floor by several dB.
A fundamental lower limit on minimum SNR for WiFi is set by the modulation type used.
Assuming BPSK or QPSK is being used (MCS0, 1, 2) then 1% BER corresponds to about 4 dB Eb/N0.
Assuming a 3 dB noise figure for the receiver of the AP and unit, and assuming the transmitter powers are equal, it seems that about
-101 + 3 + 4 = -94 dBm
should be a rough lower limit for establishing a WiFi connection.
The throughput as anyone has experienced at that signal level will be nil, but a WiFi connection can be established in the -94 dBm range.
This analysis is oversimplified, because WiFi uses OFDM with numerous subcarriers operating in parallel.
Making a minimally useful WiFi connection requires a few dB more signal strength.
If we believe the receive power indicator, -84 dBm seems to an approximate lower limit for actually being able to slowly download a website or buffer video.
Factors affecting the minimum viable WiFi signal include:
- ambient RF noise: microwave oven, Bluetooth, other WiFi traffic, baby monitors
- amount of other WiFi traffic: after-hours business vs. streaming HD video or torrents
- environmental variability: signal strengths are never constant. Desired and undesired signal strengths are always changing due to reflections from countless objects.
- equipment variability: performance of equipment varies from how it’s held, its temperature, etc.
- interference at one or both ends: If either end is in an interference area, the link is broken as both ends have to hear each other. This and the asymmetric data transfer are some reasons why we set AP transmit power a bit higher than the mobile devices.
With professional WiFi gear in greenfield (no interference) WiFi environments, I’ve seen 360p video streaming work acceptably, but with intermittent interruptions at -87 dBm.
Would I ever design a system like that?
No!
I was merely surprised to see it actually usually working like that, but giving occasional signal loss alarms.
The real question to ask when wanting to know if a system application will be viable is what is the minimum viable signal for the required data throughput and reliability factor.
To stream live video with occasional glitches at 360p in a clean RF environment, -77 dBm may be just enough signal allowing 10 dB for environmental variation.
I can’t say it would not work, but I would be doubtful about how reliable it would be for clean uninterrupted no-glitch streaming for an hour.
To cover a warehouse on the edge of a rural town for bar code readers or temperature sensors and the budget was tight, it’s possible that -77 dBm is just enough, assuming temporary outages don’t impact the business or safety, and that outages are logged.
Merely going in and designing a system for -65 dBm everywhere can be too expensive, and your competitor might get the bid instead.
Know the characteristics of the system elements you design/support/sell/maintain.
When you want to maximize performance vs. cost, you have to measure, experiment and log to verify your designs work in a wide variety of scenarios and to insure performance is met over time.
YouTube Live bandwidth requirements
Related: Manual WiFi AP config for better performance