A disruptive approach to RF interference hunting techniques

As more wideband frequency ranges are introduced to an already crowded RF spectrum, the ability to accurately monitor said frequencies is becoming an increasingly complicated but necessary task. RF interference (RFI), an unavoidable consequence of RF advancement, threatens the fidelity of sophisticated communications mechanisms operating in high band frequencies and must be mitigated if Quality of Service (QoS) is to be maintained.

RF signals and the vast range of devices, machines, and components they power have become deeply entrenched in every facet of modern life. They enable all forms of civilian, commercial, and military communications: from walkie-talkies, pagers, mobile handsets, smartwatches, body-worn technologies, and embedded sensors to industrial robots, medical robots, satellite communications, radar systems, driverless cars, and unmanned aviation vehicles (UAVs). All this technology requires wireless RF to work.

What is radio frequency interference?

Radio frequency interference (RFI) is the accidental or intentional transmission of RF energy at frequencies and levels that interfere with the operation of licensed equipment or services by blocking, jamming, or masking those legally licensed signals.

The issue, however, is that most RF-enabled hardware generates some form of RFI. The extent to which this happens depends on hardware type, design, and application. Before the “smart phenomena,” managing and controlling RFI levels was always relatively straightforward, so long as you had the know-how to improve system design and the right tools to monitor the extent of RFI.

Monitoring processes typically involved sending teams with handheld readers to site to identify different sources at ground level. However, with IoT and automation becoming key to many services, manual monitoring practices are no longer up to the job. Not only are they inefficient and resource-heavy, they pose serious accuracy risks in mission-critical situations where an undetected signal could result in a life-or-death situation. 

Wireless RF is integral to public safety and international security. But considering the total number of IoT devices is set to hit 27 billion by 2025, the task of monitoring RFI in check has become even more critical.

Not only do unwanted and unrecognized transmissions impact the quality of service for the end user, but uncontrolled RFI will also cause untold damage to TelCo and TowerCo equipment, compromise public safety communications, and disrupt autonomous applications.

What are the different types of RFI?

RFI manifests itself in many different formats. Causes can range from damaged or leaky RF cables, poor hardware design, and improper antenna positioning to frequency overlaps, timing issues, or unlawful activities. The first indicators of RFI (in commercial cellular services, at least) include crackling, humming, waterfall sounds, voices from other transmissions, jittering, or buffering—none of which make for a great user experience.

In conflict zones, RFI is deliberately generated using illegal jammers or by transmitting hugely powerful wideband RF signals intended to take down all forms of communications (a tactic currently being deployed in Ukraine). Moreover, there are also various forms of natural interference (thermal noise, shot noise, flicker noise, and phase noise).

Global digitization and RFI: a catch-22 situation

RFI, irrespective of the source, is intensifying. This puts pressure on existing services and the usable RF spectrum. In tandem, hunting down RFI and determining the cause is becoming equally challenging but essential in a wireless-enabled world.

In the commercial world, unwanted and unrecognized RF transmissions are detrimental to stakeholders that have paid hefty sums for their spectrum licenses. Any interference, deliberate or otherwise, equates to a loss of earnings for regulators and must be eliminated using intelligent spectrum monitoring technology that flags different RFI issues in real time.

RFI in conflict zones

Hunting for interference sources in conflict zones takes spectrum monitoring requirements to an entirely different level because it is highly unlikely that you will know the RFI source or how it is being transmitted. Therefore, the entire RF spectrum must be considered. Besides having wideband capabilities to enable 24/7 spectrum monitoring, the deployed spectrum analyzing system must comprise the necessary computing for real-time signal sampling. More importantly, the system must be passive so it is undetectable to the enemy.

Characterizing interference

With so many devices and components transmitting and receiving RF signals in the upper limits of the RF spectrum, the task of categorizing the different emissions is immense due to the sheer number of frequencies being used and the different use case scenarios. Those responsible for policing spectrum usage need powerful spectrum analyzing equipment that allows them quickly to determine whether the RFI source is the result of: 

• An illegal transmitter
• Signal spoofing technology
• A frequency out of spec
• A frequency clash
• Faulty equipment
• A poor connection
• Design issues 

As wireless RF replaces legacy wired services and more sophisticated signal modulation and demodulation forms are implemented, RFI must be quickly distinguished from genuine transmissions for operability, safety, and business continuity. Once the RFI sources have been identified, the deployed spectrum monitoring system must offer the flexibility to set up alarms and flags for unrecognized frequencies, thus speeding up responses and enabling insightful decisions that reflect the severity of the situation.

A disruptive approach is needed

RFI challenges will only intensify as 5G rollouts accelerate IoT and automation gains traction. In situations where RFI is constant, the quickest way to overcome the problem is to deploy handheld spectrum analyzers in the areas of concern to identify interference in real time.

However, manual processes are becoming increasingly less viable as the RFI challenge intensifies or the interference is sporadic, infrequent, and of short duration—not least because such solutions cannot capture the high-fidelity RF data levels needed for dynamic signal sampling of wideband signals.

Moreover, wideband frequencies are impacted by myriad factors, including multipath reception, line of sight interference, Fresnel zone Interference, and weather conditions, thus rendering many manual spectrum analyzers unfit for purpose. A disruptive approach is needed that enables:

• Around-the-clock monitoring of the entire spectrum to ensure nothing is missed
• Dynamic data capture for accurate signal sampling that reflects the situation in real time
• Autonomous detection capabilities for efficiency and accuracy reasons
• Proactive classification of unrecognized signals, with those of concern flagged and dealt with in real time
• The transformation of high-volume RF data into actionable intelligence

Conclusion

As more complex RF signals are introduced to the ever-crowded RF spectrum, those responsible for managing this finite resource must have the tools to monitor its usage effectively. RF interference threatens the fidelity of RF-enabled technologies, and steps must be taken to mitigate this, not just for performance and QoS reasons but to ensure public safety and national security.