The discussions and debates we heard during presentation of 5G trial results and 4G/5G device performance at the recent IWPC conference made quite clear the fact that, so far, the first 5G NR launches continue to be challenged by the testing, certification and validation of devices. This has a direct impact on device performance and their interaction with the network. As a result, the current focus of operators is to consider how should they test devices thoroughly and accurately from a technical perspective, as well as cost efficiently.
However, operators are also aware of the myriad of questions mounting up and which will need to be addressed once the first devices are available and network deployments and launches begin. In addition, it is well understood that device-based measurements (which reflect exactly how the device perceives and interacts with the network) will be the very first test cases that need to be performed.
In this second post, based on key conclusions from the IWPC conference, we share some of these key questions — and how Infovista's 5G product and solution portfolio can answer them, for both sub 6GHz or mmWave.
Q: What is my 5G NR coverage?
Infovista's 5G NR scanning solutions help generate 5G NR coverage maps for rapid visualization of 5G NR coverage and performance. In addition, in time, Infovista solutions will automatically provide feedback from scanning data to our planning tool for model tuning and accuracy improvement. Coverage evaluation, as well as automated planning model tuning, will become more crucial with 5G NR, especially for mmWave deployments. This is due to the need for the verification of coverage consistency, taking into account vegetation, weather, buildings, and dynamic obstructions.
Q: Why didn't I receive the expected 5G NR coverage (gain)?
Infovista tools will help you troubleshoot beam forming, tracking and finding, and evaluate time to acquisition. They will also reveal if beams are efficiently switched and validated, if the strongest beam has been acquired, and how beams are managed within the context of likely vendor-specific procedures.
The information will be post-processed and correlated with the selected configuration, showing the allocation of narrow beams within each wide beam to be further used for coverage optimization purposes. This is particularly important in grey coverage areas, between locations for which the beams may be aimed too high or too low towards devices. In addition, evaluation of the time to acquisition of the strongest beam can be used for optimization of handover interruption time.
Q: Do devices make a difference to coverage performance?
It is expected that devices will make a difference, for several reasons. These include: the bandwidths at which devices operate, and the power consumption needed; device housing materials; antenna location within the device; and phone sensitivity and RF front-end performance, which determines the efficiency with which reflections can be exploited to extend coverage, especially in mmWave scenarios.
Q: How can I identify and verify the differences between devices? How quickly can I perform this evaluation?
Infovista tools will help define test scenario scripts in line with the availability of different devices. They will also send remote commands from a cloud-based orchestrator for data collection from different devices placed in the field. The tools will log into these field devices and collect the required information elements that describe coverage performance. These information elements are then streamed in real-time back to the orchestrator for further processing and augmented analysis.
In addition, the whole process will be automated and optimized for different devices. The automation of these tasks will allow such tests to become part of an operator's standard set up procedures for device validation and certification. As we noted before, understanding and evaluating the interaction of 5G devices with the network is crucial for the realization of 5G NR performance. It's essential, therefore, to perform these tasks before a specific device is launched.
Q: What is the real throughput benefit of my 5G NR coverage?
As might be expected, this depends on a number of factors. First, on whether low or high spectrum is deployed. Second, on the designated bandwidth. Infovista planning tools can help you estimate the throughput gain, based on the selected spectrum-bandwidth configuration.
However — and perhaps more importantly - Infovista tools will also help you evaluate field throughput gain for the deployed spectrum-bandwidth configuration, as well as troubleshoot unexpectedly low performance.
Infovista will help answer questions such as, but not limited to:
- Is coverage impaired by interference (or even beam interference from the same TRP-transmission point)?
- Is RF quality good enough to achieve the expected throughput?
- Or, is faulty dual connectivity causing incorrect radio resource allocation to 5G NR?
In addition, the evaluation will be performed against LTE while comparing results in the same analytics window. Simultaneous evaluation of LTE and 5G NR becomes crucial for dual connectivity troubleshooting when Layer L3 messages need to be analyzed and the timing between radio accesses needs to be tracked and monitored.
Q: How can I cope with the amount of data that 5G NR deployments' test use cases come with?
Collecting and intelligently sampling out and/or aggregating the most relevant data for various 5G NR test use cases, as well as processing, visualizing and diagnosing the test results in a meaningful, automated and autonomous way — and as quickly as possible, are the minimum requirements for answering this question. Infovista cloud- and real time data streaming-based analytics tool geared towards 5G NR test use cases will help you meet these requirements using capabilities such as, but not limited to: automated symptoms and root causes detection embedded in the processing and analysis of each test use case; root causes severity ranking based on statistical analysis and significance hypothesis testing; rules based diagnosis augmented with machine learning techniques; device centric root cause analysis for devices' field performance evaluation and benchmarking as well as cost efficient optimization of 5G NR deployments.
You can learn more about Infovista's views on device rollout in 5G NR testing, as well as 5G NR test use cases in our presentation from the IWPC conference “5G Planning and Testing: A View on UE Roll on 5G Testing”
There's more to come soon. Watch this space for updates on our 5G product releases - and an exclusive white paper that will be shortly be available at https://www.infovista.com/
