FEATURE MONITORING & METERING
acquire and store large amounts of data over time. All measurement data are time-stamped and stored in a data base in a remote computer, and the software then combines all the data from each probe and determines (based on defined limits known as frequency masks) when the interference occurs prior to analysing its amplitude and locating it on a map. All measured data from each sensor on the field are recorded into the same data base on a server or a remote computer. The monitoring task is made easier by software such as Vision Monitor (Figure 4), which sorts all the data to help isolate the interferer events. Based on user- defined limits, the software is even capable of sending warning alarms by email to a chosen user. Once the interferer frequency is
From top: Figure 4: Vision Monitor showing the position of three probes on the field and the moment of time when the interferer over passes a defined amplitude limit; Figure 5a: Vision Locate software determining the position of the interferer on a map using POA technique and Figure 5b: TDOA technique showing hyperbolic curves’ intersection; Figure 6: “Heat map” showing the estimated position, the current car position and the various roads taken with the related amplitude records on the screen linked to each map’s data points
28 APRIL 2018 | INSTRUMENTATION
highlighted, two techniques are available for geographical location of the interference source (Figure 5): • The power of arrival (POA) technique: a geolocation algorithm that uses synchronous frequency-domain captures to determine and compare the instantaneous relative power of a given signal at different receiver locations (Figure 5). The calculation method will lead to the potential location of the interferer on the map. This technique is easy to apply and can be used anytime a signal is “seen” whether it is narrow or broadband. Its limitations are that it is affected by obstacles in the field and it is generally limited to use within the triangle formed by the field probes. • The time difference of arrival (TDOA) technique: an algorithm which uses synchronous time-domain captures to determine the relative time of arrival of a signal at different probe locations. The technique is optimal for geolocation over wide areas. All probes are time- synchronised with a reference time of 8ns. Unlike measurements of absolute distance or angle, measuring the difference in distance between different probes will result in an infinite number of locations that satisfy the measurement. When these possible locations are plotted, they form a hyperbolic curve. Using three or more probes in the field with this technique will result in a source geolocation probability limited to a bounded area or point. TDOA is useful only when handling modulated signals (either narrow or broadband). This technique is minimally affected by obstacles; it works outside the probe triangle; and it is much more precise than POA, with an accuracy as low as 20m. In situations where the POA or TDOA monitoring technique have not
been used, it is still possible to make a drive test focusing on the interferer signal using a measurement tool called the “mobile interference hunter” which automates the interference hunting process. In this scenario, the driven area can be quite large: for example, a cell sector of a cellular network where key performance indicators may have shown a reduction in performance over time. It then becomes necessary to drive around this area to measure the interferer frequency in order to locate it. The Mobile Interference Hunter
consists of a handheld spectrum analyser placed in a car and controlled by a remote computer via an Ethernet link, along with an off-the-shelf magnet mounted omnidirectional antenna which also integrates a GPS antenna. Software installed in a tablet will instruct the driver where to drive based on the measured information from the likely interference signal centered onto the spectrum analyser. As the vehicle drives around the area, the software algorithm will gather all signal amplitude information and will determine where to go to get closer to the source of interference. The more the vehicle is driven, the more accurate the geolocation becomes, thanks to the software (Figure 6).
CONCLUSION As all current frequency bands are heavily used and the spectrum becomes increasingly crowded, wireless applications are being bombarded by interference which can seriously impact network performances. One way to recover normal network capacities and to ensure quality of service to the end user is to monitor the spectrum to identify and locate the faulty signals. As shown in this article, remote spectrum monitoring is typically done when a system user complains of interference from an unknown source. Recordings can be correlated with time and location estimation reports from users to determine the likely sources and facilitate “spectrum fingerprint” analysis. Spectrum monitoring also serves to enforce compliance with government regulations. Police, fire fighters, air traffic control, military and emergency services must all have access to communications free of impediments and distortion. All these hunting techniques are being deployed on the field nowadays to ensure better communications quality.
Anritsu Europe
www.anritsu.com T: 01582 433200
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