The OneAdvisor 800 RF ViewerP from VIAVI Solutions uses an augmented reality (AR)-based approach to provide real-time visualization of radio frequency (RF) signals in physical environments. The system overlays RF signal strength data onto a live video feed, enabling users to identify the location, intensity, and spatial distribution of RF emissions. This AR-based representation simplifies RF analysis by transforming abstract signal data into an intuitive visual format, improving situational awareness during field operations.
The OneAdvisor 800 RF ViewerPÂ incorporates multiple tracking modes designed to analyze and isolate different types of RF interference based on signal behavior and bandwidth characteristics. In RSSI (Received Signal Strength Indicator) mode, the system is optimized for identifying persistent RF sources that remain confined within a narrow frequency band, such as continuous transmitters or localized signal leaks. Peak Power mode is used for signals that fluctuate within a defined band, making it suitable for detecting intermittent or hopping interference typically associated with spread-spectrum systems or burst transmissions. For wider spectral activity, Channel Power mode enables analysis across broader frequency ranges, supporting the identification of wideband interference sources such as power line noise, broadband jammers, or malfunctioning RF equipment.
This setup allows users to tailor RF ViewerP based on the interference profile, improving accuracy and efficiency in identifying and resolving RF issues. The flexibility in switching between modes makes RF ViewerP suitable for environments with diverse RF challenges, such as industrial facilities, wireless labs, or urban RF surveys.
For Time Division Duplex (TDD) systems, where uplink and downlink transmissions occur in separate time slots, RF analysis can become more challenging due to time-domain separation. To address this, the OneAdvisor 800 integrates advanced measurement techniques such as Gated Sweep Spectrum and TDD Auto-Gated Spectrum (TAGS) alongside RF ViewerP. These capabilities enable precise time-windowed analysis, improving the detection and characterization of interference in TDD-based networks.
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