Insights & EventsUncategorized

Cross-Sector Detection

In today’s fast-paced telecom industry, delivering optimal network performance is essential to ensuring seamless user experiences. One significant challenge operators face is cross-sector and other issues that are affecting the overall performance of the network these issues may be related to Antenna configurations, this type of issues includes but is not limited to, wrong or […]

In today’s fast-paced telecom industry, delivering optimal network performance is essential to ensuring seamless user experiences. One significant challenge operators face is cross-sector and other issues that are affecting the overall performance of the network these issues may be related to Antenna configurations, this type of issues includes but is not limited to, wrong or shifted azimuths and other wrong configurations, or maybe hardware problems that cause down sectors. At Digis Squared, we’ve taken a bold step forward by developing an advanced AI-based algorithm that detects these kinds of issues using data gathered from drive tests in no time compared with the traditional ways. This cutting-edge solution promises to significantly reduce the time it takes to improve network performance and streamline operational costs.

Understanding Cross-Sector Problem

The cross-sector problem occurs when a mobile device connects to a sector of a cell tower that is not intended to serve its location. This typically happens due to antenna misalignment, hardware problem, or wrong configuration. As a result, the device experiences degraded performance such as signal interference, increased latency, or reduced data throughput. Additionally, the network resources of the unintended sector may be strained, impacting overall efficiency. Resolving this issue is essential for improving coverage availability and enhancing user experience in mobile networks.

Why do we need such an algorithm?

The detection of cross-sector and other problems currently requires a lot of resources (time, skilled engineers, and for sure that costs a lot of money), it may take multiple hours or days for a team to be able to investigate a drive test from one cluster, and this time is proportional to the size and complexity of the network and the surrounding environment.

In addition to that, operators are trying to solve these issues as fast as possible because by solving such issues the operators can ensure solving their consequences like:

  • Network Congestion: Too many users connected to a single sector can cause overloading, reducing data speeds and overall network performance.
  • Interference: Cross-sector interference happens when neighboring sectors overlap in coverage, causing signal degradation.
  • Inefficient Resource Use: If users are connected to a less optimal sector, network resources such as bandwidth and power are not used efficiently.

Our tool aims to ensure fast and accurate detection and reporting of cross-sector and other issues to accelerate solving related network problems to enable the users to receive the best quality of service and use the network resources.

The solution:

At Digis Squared, we have developed a novel AI-based algorithm specifically designed to detect issues that we have mentioned earlier by analyzing data collected from drive tests. This algorithm leverages AI, advanced signal processing techniques, and fast processing and analytics to automatically identify when a device is connected to a suboptimal sector.

in less than a few minutes, you can have an accurate and comprehensive report about the cross-sector and other issues found in the network.

Benefits for Telecom Operators

  • Improved Network Performance: By accurately detecting and resolving these issues, operators can enhance network efficiency and provide a better user experience by minimizing interference and improving data throughput.
  • Cost Efficiency: Automating the detection of cross-sector and other problems reduces the need for manual analysis and network intervention, which can significantly lower operational expenses (OPEX).
  • Faster Optimization: With the ability to process data and generate insights with that speed, operators can implement network changes more rapidly, ensuring that the network performs optimally at all times.

Conclusion

At Digis Squared, we are committed to pushing the boundaries of network optimization technology. Our algorithm for antenna issues detection represents a major leap forward in network management, offering telecom operators a more efficient, automated, and accurate method for resolving issues and ensuring a better user experience. By harnessing AI, and multi-metric analysis, we are enabling smarter, more resilient networks that are ready to meet the demands of the future.

Stay tuned for more updates on how this algorithm is transforming networks around the globe.