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Key Challenges for 5G Networks New Radio (NR) Field Testing

Live field testing 5G networks ensure that beams are transmitting accurately to fulfil performance metrics such as throughput per cell, throughput per device, and Quality of Experience (QoE). Learn about the key challenges that mobile network operators face in this article.

Key Challenges for 5G Networks New Radio (NR) Field Testing

Key Challenges for 5G Networks New Radio (NR) Field Testing

Table of contents

5G NR Beam-Based Coverage
Field Testing Massive MIMO Performance
Scanner-Based vs UE-Based Field Measurements
Optimizing QoE on Different Network Architectures
Conclusion

5G New Radio (NR) is moving at an accelerated pace. Achieving network targets for throughput per cell, throughput per device, and quality of experience (QoE) requires live network testing to ensure beams are transmitting accurately.

Most 5G NR deployments are in the 3.5 GHz and 28 to 29 GHz frequency ranges. Both frequency ranges are new to the cellular network and require changes in radio access techniques and network architecture. Achieving higher network capacity and higher data throughputs in these new frequency bands requires massive multiple-input / multiple-output (MIMO) technology with beamforming. However, using these technologies changes the radio access from cell coverage to beam coverage, a significant difference compared to 4G radio access networks.

5G NR also introduces a flexible air interface to support the numerous types of services expected with 5G. The backhaul infrastructure must be enough flexible to handle the different types of devices and traffic loads. Many operators are moving to software-defined networking and network functions virtualization. Distributed cloud, network slicing, and self-optimizing networks are critical enabling technologies to help virtualize the network architecture and management plane to create enhanced communication capabilities. However, these technologies require new tests to optimize QoE for different 5G applications.

As 5G radio access moves from cell coverage to beam coverage, drive test needs to evolve to validate different types of services expected with 5G. These are some key challenges:

  • Drive-testing network performance when using massive MIMO and beam steering.
  • Testing QoE with new network configurations.

5G NR Beam-Based Coverage

Network coverage measurements are different in 5G NR compare with Long-Term Evolution (LTE). 5G NR uses various forms of MIMO and beams steering to improve performance with beam-based coverage.

Massive MIMO is meant for sub-6 GHz applications. It requires many more antennas on the base station, configured for multi-user MIMO (MU-MIMO). MU-MIMO systems send multiple data streams using the same time-frequency resources from the base station. Using the massive number of antennas improves MU-MIMO performance, increasing total cell capacity.

With the use of MIMO and beamforming, there is no cell-level reference channel from which to measure the coverage of the cell. Instead, each cell has one or more synchronization signal block (SSB) beams, as shown in Figure 1. The maximum number of SSB beams per cell is between 4 – 64 depending on the frequency range. SSB beams are static or semi-static which always pointing in the same direction by forming a grid of beams covering the whole cell area. The user equipment (UE) searches for and measures the beams to maintain a set of candidate beams. The candidate beams may contain beams from multiple cells. The key metrics measured are reference signal received power (SS-RSRP), reference signal received quality (SS-RSRQ), and signal-to-interference-plus-noise ratio (SS-SINR) for each beam. Infield measurements, both scanning receivers and test user equipments can collect mentioned metrics.

Figure 1. Slot structure of SSBs mapped to a grid of static or semistatic SSB beams

Figure 1. Slot structure of SSBs mapped to a grid of static or semi-static SSB beams

Different SSB beams of a cell transmit at different times to avoid intracell interference among the SSB beams. Therefore, scanning receivers can detect very weak SSB beams, even in the presence of a dominant from the same cell. In general, the number of reference signals in the air will increase. As an example, imagine a place of feeble coverage in an LTE network, where a scanner or a test UE detects reference signals from six cells. If it were a 5G NR network, the device could see, for example, six beams of six cells each, for a total of 36 reference signals.

Field Testing Massive MIMO Performance

Massive MIMO is a cell capacity feature for sub-6 GHz 5G NR. The performance of a massive MIMO implementation has a significant impact on the system capacity of the 5G NR network. This is one area where network equipment manufacturers can best differentiate themselves from competitors. Verifying the field performance of massive MIMO implementations is a essential part of the network acceptance processes and vendor selection. Massive MIMO capacity gain occurs when multiple UEs generate downlink traffic simultaneously. Many variables impact the actual gain provided by massive MIMO.

The spatial distribution of UEs has a significant impact. Ideally, the UEs should be scattered across the cell area. It becomes impossible to isolate the users to different non-overlapping beams if all users are in the same location. The minimum acceptable horizontal and vertical spatial separation between UEs may differ depending on the number of physical antenna elements in the base station antenna panel in the horizontal and vertical dimensions. The signal-to-noise ratio of each user, as well as the multipath propagation profile, impacts the achievable performance. Every one ms (slot), the base station makes the scheduling decisions and determines whether to use MU-MIMO.

Testing the capacity gain of massive MIMO requires multiple test UEs distributed in the cell area, each performing simultaneous active bulk data transfer against a test server. In a test setup, it is crucial to ensure that core network and back-end server have enough bandwidth so that radio interface is the only bandwidth bottleneck present during the test. Using multithreaded data downloads in the tests can remove any adverse effects of Transmission Control Protocol flow control. One test scenario involves arranging UEs close to each other to test the threshold for spatial separation, where massive MIMO can still provide gain. Other scenarios include vertical distribution of UEs (such as one on each floor of a high-rise building), horizontal distribution of UEs, line-of-sight UEs versus non-line-of sight UEs with rich multipath propagation environment, moving UEs, cell edge versus cell centre, or any combination of the above.

A measurement solution consists of various types of field test units performing a driving test or walk test (Figure 2). Equipment serving as field test units includes scanners, a single UE terminal, and a PC-controlled chassis housing multiple test UEs. Test solutions should be able to monitor the data live or take the data captured back to the lab for post-processing. Post-processing of the data facilitates more in-depth analysis to find blind spots, pilot pollution, spillage, and other coverage issues. Postprocessing enables calculation of additional cell-level key performance indicators (KPIs) such as cell throughput.

Figure 2. 5G NR-ready testing solution for massive MIMO with post-processing example showing throughput

Figure 2. 5G NR-ready testing solution for massive MIMO with post-processing example showing throughput

Scanner-Based vs UE-Based Field Measurements

5G NR drive testing can use both scanners and test UEs. In legacy systems, scanners were best suited for coverage measurements because they could measure all cells from all networks in one instance. Scanners can test for in-band and out-of-band interference in the network. A UE is always associated with one operator. Constrained by the neighbour list definitions in the network, it does not necessarily measure all technologies or even all carriers. The same reasoning is valid in 5G NR. Scanners can measure the SSB (PSS, SSS, and physical layer broadcast channel, or PBCH, block) beams, the basic coverage measurement of the 5G NR network.

Figure 3. Example 5G NR scanner measurements showing coverage and quality metrics, including SS-RSRP, SS-SINR per each SSB reference beam of a cell

Figure 3. Example 5G NR scanner measurements showing coverage and quality metrics, including SS-RSRP, SS-SINR per each SSB reference beam of a cell

There are a few differences when using scanners in 5G NR compared with legacy technologies. In Wideband Code Division Multiple Access (WCDMA) and LTE networks, scanners can read the full system information: global cell ID, mobile network code, mobile country code, and other useful network parameters. In 5G NR, only the bare-minimum system information is broadcast in the common PBCH that is part of the SSB block. This avoids common, always-on cell-level transfer and minimizes the energy consumption of the network. The rest of the system information goes to the UE on-demand upon the establishment of the connection. Because of this, 5G NR scanners cannot read the full system information from the cells they are scanning.

Another consideration is that scanner antennas have different characteristics than mobile UE antennas. This was a consideration in LTE, along with the MIMO antennas, and is even more critical in 5G NR. Early 5G NR UEs implement coarse beamforming at the device end, making antenna gain and MIMO performance even more dependent on the devices.

Therefore, most live network testing uses both scanners and candidate UEs. Scanners capture the SSB reference beam coverage and provide agnostic coverage measurements. UE terminals validate performance for dual connectivity and UE mobility, including beam switching and handovers between cells.

Optimizing QoE on Different Network Architectures

Network slicing is a new concept in 5G NR for both core network and radio access networks (RANs). Network slicing allows the creation of multiple virtual networks on top of common shared physical infrastructure. A single physical network can be sliced into multiple virtual networks that can support different RANs, or different service types running across a single RAN. Network slicing replaces the quality of service (QoS) profiles used in LTE and universal mobile telecommunications. One big difference from the legacy technology is that the network automatically detects the type of application. Consequently, the network can apply separate QoS settings for different applications. For example, the network could detect a WhatsApp call as a voice-over-IP (VoIP) service and relay the traffic on a network slice that is optimized for low-latency, guaranteed low-bitrate traffic.

Figure 4. Identifying points of failure with 5G NR end-to-end QoE field test

Figure 4. Identifying points of failure with 5G NR end-to-end QoE field test

This means that a 5G NR network with network slicing operates differently depending on the application in use. Consequently, making bulk data transfers using File Transfer Protocol (FTP) or Speedtest.net does not give an accurate picture of the true QoE. Active QoE testing using real applications is thus increasingly important in 5G NR. Operators need to do network optimization or network benchmarking with live applications to find out where issues might occur.

The only way to assess end-to-end QoE in 5G NR accurately is by using active tests conducted at the device end, as shown in Figure 4. The three crucial, measurable KPIs related to the QoE of any type of transaction (retainability, accessibility, and time to content) are visible and measurable only at the device end. Active tests using real over-the-top applications are the best way to measure them.

It is essential to test the latency and peak throughput of the connection. Conducting root-cause analysis pinpoints the location of the connection bottleneck: device end, RAN, core, or back-end server. This type of analysis can also help identify points of failure for dropped calls or handover issues, for example. New test schemes should provide QoS prediction on a mean opinion score scale for different application types, including VoIP, streaming video, live TV, and web browsing. The QoS prediction allows for a quick check of 5G NR end-to-end performance with different types of applications without the need to check the QoE by the application.

Field testing (drive testing) at the application layer can translate the user experience into measurable KPIs and speed up the field verification of 5G NR use cases.

Conclusion

Live network testing of 5G NR networks ensures network coverage and QoE. For field verification, changes in radio access with beam-based cells introduce a new testing methodology that requires both scanning receivers and test UEs. A scanner is a useful tool for SSB reference beam coverage measurements. Verification of the rest of the functionalities — including traffic channel beams, QoS / QoE, mobility, and LTE interoperability — requires UE-based active field testing (drive testing).

NR QoE testing is also more complicated because of changes in the network architecture. Networks will have the ability to detect different traffic types and relay data streams from different applications to disparate QoS settings (slices). Therefore, traditional testing like Speedtest.net or FTP bulk data transfer does not reflect the true service quality as seen by an application. Conducting QoE field testing at the application layer can address the 5G NR QoE measurement challenge and translate the user experience into measurable KPIs.

Source: Keysight Technologies

Alex Lim is a certified IT Technical Support Architect with over 15 years of experience in designing, implementing, and troubleshooting complex IT systems and networks. He has worked for leading IT companies, such as Microsoft, IBM, and Cisco, providing technical support and solutions to clients across various industries and sectors. Alex has a bachelor’s degree in computer science from the National University of Singapore and a master’s degree in information security from the Massachusetts Institute of Technology. He is also the author of several best-selling books on IT technical support, such as The IT Technical Support Handbook and Troubleshooting IT Systems and Networks. Alex lives in Bandar, Johore, Malaysia with his wife and two chilrdren. You can reach him at [email protected] or follow him on Website | Twitter | Facebook

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