January 05, 2026

CTS 381: Deep Dive: Using Spectrum Analysis Tools

43 minutes

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The video is an episode of the Clear To Send podcast, hosted by Rowell Dionicio and Francois, where they discuss spectrum analysis tools.

Summary of Spectrum Analysis Discussion:

What is Spectrum Analysis? A spectrum analyzer measures activities on the RF layer (Layer 1), specifically for the 2.4 GHz, 5 GHz, and 6 GHz frequencies that Wi-Fi uses. It measures the signals and their amplitude, showing which frequencies or channels are busy and how often they are used (duty cycle or channel utilization).

Purpose: Spectrum analysis is used by Wi-Fi engineers for tasks like Wi-Fi validation surveys and troubleshooting. The goal is to see if everything is taking place normally, understand what Wi-Fi traffic looks like, and spot non-Wi-Fi traffic (interference) that could be impacting Wi-Fi.

On-Site Requirement: Spectrum analysis usually requires being on-site to find the source of interference in the real world.

Tools: For accurate analysis, a dedicated spectrum chipset is needed, as general Wi-Fi network interface cards (NICs) often only estimate channel utilization rather than provide an accurate measurement. The dedicated tools, such as the Ekahau Sidekick, offer higher resolution and faster scanning.

Visualizing the Spectrum (using the Ekahau Sidekick):

Density View: Shown at the top, it plots frequency (x-axis, Wi-Fi channels) against amplitude (y-axis, in dBm). Colors in the density view indicate how busy the channels are (e.g., orange is 50% busy, red is 100% busy).

Waterfall View: Records measurements over time, showing the evolution of the spectrum. Colors in this view indicate the strength of the signal, with red meaning the analyzer is close to the source. This view is good for identifying if a device is always transmitting on the same channel or hopping around, and when a device is transmitting.

Signal Shapes: An important piece of information is the shape of the signals, as each device generates signals with a specific shape. The speaker recommends learning to recognize these shapes, such as the Orthogonal Frequency-Division Multiplexing (OFDM) signature of Wi-Fi.

Wi-Fi Traffic Example (5 GHz): When a speed test was initiated on an iPad, the spectrum analyzer showed a strong, busy 80 MHz wide channel. The channel utilization rose to the 90s temporarily. The speed test also clearly showed the OFDM shape of Wi-Fi, including a characteristic dip in the middle.

Non-Wi-Fi Interference Examples:

Factory Lights: An interference case in a factory showed a jagged mountain shape of activity across the entire UNII-3 band (Channels 149, 153, 157, 161, 165) that was 100% busy. This was caused by motion detection sensors likely associated with the lights. The solution was to exclude those channels from the Wi-Fi channel plan.

Video Transmitters (6 GHz): Interference that looked like busy Wi-Fi traffic (having the OFDM shape) was detected in the 6 GHz band. This was from video transmitters connected to a cameraman's camera, sending a live video feed, and it was using the channel nearly 100% of the time.

Drone: A drone, when turned on, generated a steady 20 MHz wide, OFDM signal on a 5 GHz channel, sitting on top of the host's 80 MHz Wi-Fi channel and utilizing 50% of the channel.

DJI Mic (2.4 GHz): The microphone system was seen hopping across four narrow channels (2-3 MHz wide) in a pattern.

Microwave: A microwave oven can show a lot of spectrum activity, which could indicate a need for replacement if the shielding is not adequate.

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Clear To Send: Wireless Network Engineering

By Rowell Dionicio and François Vergès

4.8

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