Visualizing network performance: Ericsson's Transport Automation Controller with AI/ML at the helm
The Ericsson Transport Automation Controller uses AI and ML to visualize network performance, identify interference and fading events, and proactively manage a transport network.
Customer Solutions Sales Director – Transport
Customer Solutions Sales Director – Transport
Customer Solutions Sales Director – Transport
How AI-driven transport automation helps optimize network performance
With vast amounts of data and the need for proficient data management and handling skills, optimizing network performance becomes even more challenging. Leveraging extensive data to train artificial intelligence (AI) for microwave links has become crucial in enhancing network efficiency and experience in interpreting intricate performance charts is essential. In response to these challenges, the Ericsson Transport Automation Controller has emerged as a powerful AI tool designed to address these complexities and visualize network performance in intuitive, and easy-to-use dashboards. Microwave radio technology has long been used to offer fast installation and reliable performance in all its applications across several industries.
Transmission engineers design microwave paths using microwave radios that meet target quality and availability objectives, typically expressed in terms of how much time the radio link will be unavailable per year. Several metrics play a role in determining the quality and availability of a radio link, one of which is the power strength of the incoming receive signal level (RSL) at the receiver station that must reach a nominal target value.
The radio frequency (RF) power, or RSL strength, at the receiving station is never constant, and suffers variations over time (fading) due to changes in the path it travels, including atmospheric refractivity changes.
Figure 1 captures RSL values from a single microwave radio transmitter over three hours. Small power level variations (scintillations) of a fraction of a dB are caused by minor changes in the atmosphere’s refractivity index and are not a concern from a performance perspective.
Figure 1: Receive Signal Level (RSL) of a microwave radio. Source: Ericsson Transport Automation Controller
Maintaining optimal signal strength
To ensure optimal radio link operation, maintaining a “stable” horizontal signal strength around a target nominal RSL is essential.
Different fading events attenuate the RF power reaching the receiver station. The severity of fading events usually increases with frequency or path length and can take the radio link out of service. Tracking RSL values over time is the most effective way to understand a radio link's performance and response to various fading events quickly and efficiently.
Fading events and space diversity
Figure 2 shows a hypothetical received signal level graph, highlighting various fading events that affect the radio link's performance. The space between the green line (nominal RSL) and the dotted black line (Threshold BER 10 -6), represents the link's tolerance to fading. The red line (RSL) dropping below the threshold indicates performance degradation and a radio link outage.
Figure 2: Hypothetical Receive signal level (RSL)
Water vapor and oxygen are the main elements that absorb energy from electromagnetic waves. For frequencies up to 5 GHz, this absorption is negligible. Even up to 10 GHz, rain doesn't cause much attenuation compared to other factors. However, above 10 GHz, rain becomes a significant source of attenuation, increasing with frequency. Therefore, frequencies above 18 GHz are often used for short-distance hops.
One common fading event in long microwave radio links operating at 13 GHz and below is multipath fading, where the RSL at the receiver station consists of several signals arriving over different paths (that is, direct and surface reflected), causing signal distortion and degradation.
Space diversity, placing two antennas per site vertically separated, counteracts multipath fading. A strong RSL value reaches the diversity antenna when the signal at the main antenna fades.
Figure 3: Main and diversity radios receive signal level
As shown in the RSL data in Figure 3, the diversity signal (blue line) reaches a strong RSL value, demonstrating an up-fading phenomenon where the signal strength exceeds normal levels. At the time the blue line peaks, the signal from the main antenna (green line) experiences fading. This behavior not only highlights the effectiveness of space diversity, but also indicates a well-engineered antenna center line height design for both the main and diversity antennas.
Atmospheric effects and seasonal variations
A microwave radio signal traveling from point A to point B traverses an atmosphere susceptible to varying weather conditions that impact its trajectory and strength. Variables like temperature, air pressure, and humidity at different heights affect the signal propagation and strength reaching the receiver station.
These atmospheric effects drive daily and seasonal fading events, making it essential for microwave service provider to understand the radio link's performance over time.
Data management and Ericsson Transport Automation Controller
Service providers deploy multicarrier and multiband booster solutions to increase radio link capacity, increasing the number of radios per path and compounding data management challenges.
Based on the RSL charts presented in the earlier figures, it is evident that the volume of data generated from a single microwave radio is significant, requiring both data handling skills and field experience to interpret RSL patterns.
To assist with data collection, analysis, and interpretation, Ericsson has introduced the Transport Automation Controller , an intelligent, cloud-native transport automation software solution that uses AI and machine learning to provide advanced analytics and automation for microwave, IP, and optical networks.
Trained on large microwave networks for years, the transport controller can interpret different RSL patterns, and infer reasons for problematic links.
Use cases and benefits of the Transport Automation Controller
One use case of the transport controller is identifying paths subject to interference. Interference is detected when RSL values are at expected levels for both transmit directions, but there is a noticeable performance drop in the Signal to Noise Interference Ratio (SNIR).
Figure 4: Ericsson Transport Automation Controller RSL interference detection
Figure 4 presents charts showing RSL performance and SNIR ratio for a path. Stable RSL values but consistent SNIR drops suggest interference starting on 10-22, possibly caused by a nearby misconfigured radio or external interferer.
The Ericsson Transport Automation Controller provides a graphical map indicating which site is experiencing interference, guiding service providers on where to look. Moreover, the transport controller will also provide valuable insights into the root cause of the interference, helping them take the right actions when and where needed. Another fading event affecting microwave networks is rain fade, where rain reflects RF energy, reducing the RSL at the receiver end.
Figure 5: Rain Fade from Ericsson Transport Automation Controller
Figure 5 shows rain starting to affect the RSL value around 14:09. The red RSL line shows a gradual decline in signal strength until about 8:11, corresponding to increased rain intensity. Heavy rain can quickly degrade the RSL signal and cause short-term outages depending on the frequency.
The complexity of interpreting signal-strength variations along a microwave path is simplified through machine learning and artificial intelligence in the transport controller. Its intelligence performs pattern recognition of RSL values, providing microwave operators with clear insights into the reasons behind specific microwave path behaviors.
In addition, the Transport Automation Controller’s pattern recognition translates into time and cost savings, by reducing troubleshooting time, eliminating unnecessary site visits, and allowing network operations center (NOC) engineers to focus on preventive actions that enhance network quality and performance. As the microwave network grows, the more paths monitored by the transport controller, the greater the cost savings for the service provider.
To facilitate quick access to all paths monitored within the service provider's network, the Transport Controller provides a geographic map where each path is represented as a straight line, drawn using actual latitude and longitude coordinates. These lines are color-coded according to the root cause of a fading event. Users can zoom in for a closer view, allowing them to access detailed information about each path and its behavior as interpreted by the controller.
Summary
In the blog, we discussed challenges associated with maintaining stable signal strength of microwave links for optimal performance. It highlighted the impact of fading events, such as multipath fading and rain fade, on radio links and emphasized the importance of tracking signal strength variations over time, including interpreting data from microwave networks quickly and efficiently. Ericssons Transport Automation Controller is a cloud-native software solution that utilizes AI and machine learning to analyze microwave, IP and optical networks, helping service providers to save time and costs while improving network performance. Overall, the role of advanced analytics and automation is crucial for managing the complexity of microwave radio networks.
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