Spectrum Monitoring Software

Spectrum monitoring aids in network protection and maintenance as elusive events undermine spectral security and crowded spectrum results in increased interference. Governments around the world do their best to regulate the electromagnetic (EM) spectrum, assigning specific frequency bands to certain communications applications. As these frequency bands become more crowded, networks are more likely to experience interference or even communications failure. These challenges arise from any radio-frequency (RF) system, including cellular phones and drones. These intentional or accidental signals can wreak havoc on a wireless system, creating issues such as noise in the channel or even loss of service.

Spectrum monitoring allows you to detect and locate interferers in cellular and satellite communications while reinforcing key tactics to mitigate interference. In today’s crowded RF spectrum, interference is a frequent and unpredictable threat to performance and security. You need tools to help you detect, classify, and locate it quickly and accurately.

Software can detect, identify, and provide a location of interfering signals using a unique RF fingerprinting algorithm. Discovery of that fingerprint anywhere in the spectrum can trigger geolocation, which leads to the emitter location. Another approach involves using a handheld analyzer in conjunction with geolocation software. The goal of spectrum monitoring and signal analysis is to detect, identify, locate, and report problem signals in your spectrum.

Keysight Spectrum Management Software (KSMS) works with Keysight’s FieldFox RF and microwave analyzers so users can set up a signal monitoring network to monitor RF spectrum activities, report frequency allocation and usage, detect interference, and locate problem signals using Time of Difference of Arrival (TDoA) and Received Signal Strength (RSS) techniques.

Spectrum monitoring requires constant trade offs between dynamic range, wider bandwidths, and sweep speeds. Just because technology allows you to grab a gigahertz of the spectrum, it might not be the best approach. A larger and wider chunk of the spectrum means more environmental noise. The noise floor rises, limiting the selectivity or sensitivity of the front end. You will then struggle to single out signals that might be miles away.

Dynamic range is not an issue if the problem signal you seek is fairly high in amplitude and causing problems. With a high-amplitude signal, you can grab a huge chunk of spectrum. The noise floor is not a concern, as the problem signal will show in that wide chunk of spectrum. In contrast, if a low amplitude signal is causing problems, you can divide the spectrum into smaller steps. This approach reduces the noise floor, making the signal visible.