Test Talk

PCI Express® Cruises the Automotive Fast Lane

June 30, 2021

According to market analysts, the autonomous car market will rise from $20.97 billion in 2020 to $61.93 billion in 2026, for a CAGR of 22.75%, during the five-year timeframe.¹ Given this expected growth rate, verifying advanced driver-assistance systems (ADAS) will take on greater importance.

ADAS is also one reason PCIe® architecture is expanding rapidly in automotive designs. With the latest PCIe generation – 6.0 – the use of the technology will only become more prominent, especially in autonomous vehicles.

Why is PCIe racing to the interconnect lead in advanced vehicle designs? Three main reasons:

Bandwidth – The latest PCIe 6.0 specification increases bandwidth to 64 GT/sec. PCI-SIG® is committed to continuing the bandwidth doubling shown in Figure 1 in future specifications, allowing it to support emerging automotive technologies.

Figure 1: PCIe data rates by generation.

Connectivity – PCIe hardware guarantees data packets will be transferred to the desired destination, unlike other interconnects that rely on software. Plus, PCIe has much lower latency capabilities than alternatives such as Ethernet.

Ecosystem – There is plenty of off-the-shelf silicon that utilizes PCIe technology, ranging from Wi-Fi chipsets to 5G modems. This field-proven track record includes infotainment and navigation systems used in connected cars.

Overcoming the Complexity Roadblock

The doubling of data rates and other performance upgrades of PCIe 6.0 adds complexity to high-speed interconnects used in automotive designs. Engineers need signal integrity tests and analysis tools to verify products comply with PCIe 6.0 standards.

PCIe 6.0 utilizes 32 Gbaud PAM4 signaling. Though the underlying frequency is the same as the PCIe 5.0 specification, there is extra circuitry and logic involved for PAM4 to track three eyes, along with the logic changes to operate in Flow Control Unit (FLIT) mode. Because error correction happens on FLIT, cyclic redundancy check (CRC) and retry must take place at the FLIT level.

Because PCIe 6.0 has three eyes in the same UI, eye height and width are reduced. BER will be several levels of magnitude higher with PAM4 as a result, which is why Forward Error Correction (FEC) is necessary.

FEC Importance

PCI-SIG established a low-latency FEC of <2 nsec for PCIe 6.0, and it will be part of the specified overall signal latency of <10 nsec. FEC is based on a fixed number of symbols, making it simple to transition to FLITs, as they are fixed size, as well.

FEC logic is expected to operate at 1G (or 500 MHz or 2G) and easily reach a latency exceeding 2 nsec. PCI-SIG recommends a lightweight FEC for correction. The robust CRC for detection, combined with a fast link-level replay, handles any errors that the FEC cannot correct. As long as the replay probability of a FLIT is approximately 10-6, there is no appreciable performance impact either from the FEC latency or the replay latency in case of an undetected error.

A recommended approach is to establish a FEC symbol error threshold. To set a threshold, a bit error rate tester (BERT) generates a PAM4 signal to the Device Under Test (DUT) receiver input. The DUT determines the logic state of the input signal and loop decision to transmitter output for the error signal in the BERT for analysis. The BERT’s built-in Error Detector (ED) determines if the DUT’s decision was correct. For relevant results, the BERT’s jitter and noise profiles must comply with standards.

Link Equalization Factors

Link training and stressed receiver tolerance are simultaneously evaluated using a stressed signal in the link equalization test. Tests for receivers and transmitters must take place using SigTest software developed by the PCI-SIG.

Receiver link equalization testing (figure 2) has one notable difference from a standard stressed-eye receiver BER. The DUT must first perform link negotiation to correctly compensate for the test channel. The idea of stressed receiver tolerance testing is to send the DUT-receiver the worst-case signal that still complies with the specification.

Figure 2: Receiver link equalization test configuration.

Prior to conducting the test, the signal transmitted from the BERT must be precisely calibrated to generate the worst-case signal at the end of the test channel. The test signal has jitter and interference impairments that include random jitter (RJ), sinusoidal jitter (SJ), sinusoidal differential mode interference (DMI), and common mode interference (CMI) through loss channel intersymbol interference (ISI).

Transmitter link equalization testing (figure 3) is a required compliance test that verifies the device correctly changes equalization within the specified time when the link partner requests it. The BERT requests an equalization change from the devices that simultaneously sends a trigger to an oscilloscope, so the time delay to the DUT can be measured in the electrical domain.

Figure 3: Transmitter link equalization test setup.

Selecting Proper Test System

To conduct these measurements accurately, PCIe 6.0 test systems need a feature-rich, protocol-aware BERT, along with an oscilloscope. The BERT needs a built-in instrument-quality Pulse Pattern Generator (PPG) that can apply precise levels of specific signal impairments and a built-in ED capable of verifying compliance with the PCIe specifications. The BERT should have multiple NRZ pattern-generating channels and error detectors that operate at 32 GT/sec and PAM4 channels at 64 GT/sec to support PCIe 6.0 and earlier generations.

Low intrinsic jitter of 115 fsec and 12 psec 20 to 80% rise/fall times are also necessary for signal integrity. The BERT must apply every required signal impairment in amplitude ranges that exceed those required by the PCIe 6.0 specifications,

The built-in ED of the Signal Quality Analyzer-R MP1900A has FEC analysis functions to detect FEC symbol errors based on the 400 GbE FEC standard. Bit error changes and FEC symbol errors with alterations in input amplitude and jitter conditions can be monitored in real-time to quickly and reproducibly conduct evaluations when symbol error counts exceed the correction ability of FEC.

You can learn more about PCIe 6.0 and how to solve associated testing challenges by downloading an application note on the topic. For advanced automotive design solutions, you can also download a TU Automotive e-book.

Source:
1 Autonomous/Driverless Car Market – Growth, Trends, COVID-19 Impact, and Forecast (2021 - 2026); Mordor Intelligence

The Rise of Autonomous Technology in the Military and What it Means

August 30, 2022

The integration of 5G technology in the military, which we discussed in a recent post, will influence every aspect of warfare. In particular, it will have a major impact on the implementation of an autonomous force. While creating scenarios straight out of a science fiction movie is a popular narrative, the reality is that autonomous technology will more likely impact intelligence gathering and medical care more than create an army of Terminator robots marching on the front lines.

Given the mission critical nature of these use cases, ensuring their operation in the harshest environments is a necessity – and a challenge. That is why those responsible for the design and utilization of these autonomous solutions must establish the proper test process to ensure operation whenever they are called upon.  

Figure 1: Autonomous technology is changing modern warfare.

Bleeding-edge technology has become a vital weapon in today’s modern warfare faster than previous generations, due in large part to a philosophy of leveraging commercial 5G technology. Helping with this approach is the Defense Innovation Unit (DIU), which has a charter to strengthen national security by accelerating the adoption of commercial technology into the Department of Defense (DoD).  

Autonomy Use Cases

Autonomy is one of six focus areas for DIU in its work with the military. Separately, research has shown that autonomous technology can be used to create benefits in all functions, from intelligence to cyber security and all-domain warfighting. Familiar examples of this include:

Troop Deployments – Autonomy will be used on the front lines but not in the way we see it in the movies. Recognizing that the primary benefit of autonomous systems is safety, one use will be to replace manned reconnaissance patrols. Autonomous systems have another strategic advantage: They can act as force multipliers. So, the Army can add to its combat power while simultaneously requiring fewer troops.

One application for autonomous technology on the battlefield is for equipment transport. The Squad Multipurpose Equipment Transport (SMET) is a robotic vehicle that trails a dismounted squad carrying much of the 60-120 pounds of gear troops presently lug around. SMET utilizes follow-me and waypoint navigation, with full obstacle detection and avoidance.

Another important effort is the Future Vertical Lift (FVL) aircraft, the next generation of rotorcraft that will operate at faster speeds, have longer range, and higher payloads. Autonomous flight capabilities will be a big element of FVL. SMET and FVL, as well as other autonomous military vehicles may utilize Vehicle-to-Everything (V2X) communications to navigate through the terrain and perform their respective mission roles. 

Medical Treatment – Keeping with the emphasis on safety is how autonomous technology will improve first-aid in the field. Currently, mobile medics are deployed to active zones to treat wounded soldiers. Combining 5G and autonomous technologies allows advanced medical expertise to be sent into those life-threatening environments when necessary, with far less risk to medical professionals. Research is being done on medical robots to evaluate their ability to assist deployed troops, as well as to establish low latency connectivity in war zones for telemedicine and telesurgery. 

Figure 2: Intelligence gathering and monitoring is enhanced with autonomous technology.

Intelligence Gathering – Not surprisingly, acquiring and analyzing intelligence will benefit from emerging technologies, including autonomy. It goes beyond the decades-proven advantages of unmanned aerial vehicles (UAVs). One example is autonomous software codes being used to gather intel by monitoring cyberspace.

There are also autonomous systems under development by the U.S. Special Operations Command to further improve its full intelligence process. Autonomous systems are expected to be used for computationally intensive tasks. It will add reliability and confidence by reducing the chance of human error. Analysts are using autonomous systems to more effectively collect and process data overall, as well.

Ensuring Operation in Harsh Environments

Similar to military autonomous use cases leveraging emerging commercial technologies, effective test processes will also borrow from established non-military applications. Assessing and understanding key aspects of such operations – especially in a highly dynamic environment – is critical to the success of autonomous systems and their ability to operate as they were designed. Consequently, test solutions must be highly accurate to meet specific testing requirements in autonomous designs. This is accomplished through:   

• Connectivity of various technologies to ensure system operation
• Hardware-in-the-Loop (HIL) to create simulations to verify control systems performance
• Data throughput and handovers
• Application of standards and regulatory requirements

Due to the critical nature of these systems, test solutions must have high accuracy and high-end performance. For example, conventional spectrum analyzers have a degraded noise floor above 3 GHz because they use a pre-selector at the 3-GHz basic band, which lowers accuracy. The Anritsu MS269xA signal analyzers have a basic band of 6 GHz that eliminates the degraded noise floor and improves measurement results.

Figure 3: The Signal Analyzer MS2850A has the performance necessary to verify advanced military systems.

The Signal Analyzer MS2850A (figure 1) has amplitude and phase flatness performance over a wide 1 GHz analysis bandwidth that exceeds other signal analyzers. It has a high ADC clipping level over the analysis bandwidth to obtain a wider difference from the DANL. This improved dynamic range performance helps obtain more accurate EVM values when measuring 5G signals.

Further aiding in 5G analysis is the Radio Communication Test Station MT8000A test platform that supports Frequency Range 1 (FR1) and Frequency Range 2 (FR2). It can be integrated with SmartStudio software so various functional tests can be performed via GUI without requiring difficult scenario development, so the MT8000A can be easily enhanced to address future military system designs.

5G will play an important role in a new generation of military and defense systems. Anritsu recognizes the military has many specific requirements related to 5G rollout. As part of its commitment to the Armed Forces, Anritsu is a member of the National Spectrum Consortium (NSC), where it collaborates on the research, development, and implementation of 5G-based technologies. As an NSC member, Anritsu works with fellow member companies and senior government officials to help shape 5G and electromagnetic spectrum management, which promotes the development of test solutions to satisfy emerging military designs.

To learn more about the technology, you can watch this 5G Technology & Concepts webinar.

Importance of OTA Measurements in 5G NR Device Verification

May 18, 2021

5G New Radio (NR) continues to be rolled out at an exponential rate. According to GSA, there were 756 announced 5G devices as of April 30, 2021. This is a 28.6% rise compared to the number of announced devices at the end of January.

Device availability is growing at an equally impressive rate. As of April 30, 468 5G devices were commercially available. This represents an increase of 28.2% since the end of last quarter. Slightly more than half (51.2%) of those devices are mobile phones.

Figure 1: Number of 5G devices, as of April 30, 2021 (courtesy of GSA).

Ensuring 5G NR UE operability as it is commercialized requires a greater emphasis on over-the-air (OTA) testing. OTA testing has been a verification method of 4G cellular technology since its deployment and standards adoption. It has gained more emphasis in 5G UE design due to the integrated nature of transmitters and the expanded use of millimeter wave (mmWave) spectrum.

5G Use Cases

To better understand the importance of OTA testing, it’s helpful to consider the advanced use cases associated with 5G:

• eMBB (enhanced Mobile Broadband) is focused on high throughput and supports high speeds from 5-20 Gbps. It is geared towards data-driven use cases in need of high data rates across a wide coverage area.
• mMTC (massive Machine Type Communications) addresses the explosion of devices in a variety of use cases and associated connectivity challenges. It can support up to 1 million devices per square km, including those that only send data sporadically. mMTC is particularly well suited for IoT environments.
• uRLLC (Ultra Reliable Low Latency Communications), with its 1 ms latency, is for mission critical use cases that demand extremely high reliability. Think remote surgery and autonomous vehicles.

Figure 2: 5G use cases (image courtesy of ITU).

OTA Measurement Fundamentals

As mentioned earlier, OTA measurements have been a conventional technique for 4G cellular device verification. Performance evaluations, antenna measurements, and MIMO verification are done via OTA.

For 5G NR, there are three main OTA tests to measure key UE characteristics:

EIRP (Effective Isotropic Radiated Power) is the total power radiated by a hypothetical isotropic antenna to give the same signal strength as the actual source in a single direction. Positive dBi values indicate gain; conversely negative dBi values represent loss.

EIRP CDF (Cumulative Distribution Function) is a combination of transmitted power and array gain. It measures power distribution at every angle. This evaluation is conducted to determine spherical coverage.

TRP (Transmission/Reception Point) is a measurement of radiated power at all possible angles. It is done to evaluate emissions, such as error vector magnitude (EVM). It is noteworthy that TRP can be calculated from EIRP.

A three-step test procedure is used to conduct these measurements:

1. Lock the UE transmission beam
2. Adjust the azimuth and evaluation angle
3. Conduct the respective power measurement

Determining Measurement Distance

To ensure accurate measurements, the appropriate distance between the device-under-test (DUT) and measurement point must be established. Typically, OTA tests are conducted in either the near-field or far-field regions of the antenna array (figure 3). With far-field regions, the distance between UE to the measurement antenna is sufficiently far enough that there is no influence on the directional characteristics. The waves are approximated as plane waves at the measurement point. If the distance between the two is not far enough, it is considered to be in the near-field region, also known as radiative near field. In this scenario, the measurement result may be distorted by the measurement antenna.

Figure 3: Visual depiction of near- and far-field areas in an OTA testing environment.

Far-field conditions are typically achieved in one of two ways – Direct Far Field (DFF) or Indirect Far Field (IFF), which are outlined in figure 4. To create a DFF condition, the measurement distance must be greater than the far field distance. The only drawback to this approach is that as devices become larger, the test chamber needs to be bigger. This can increase cost and become tenable in a confined lab space. An example of an RF chamber for DFF is the MA8171A. It can be for conformance and protocol tests, such as 5G NR beam management.

IFF, also referred to as Compact Antenna Test Range (CATR), utilizes reflecting mirrors to generate plane waves at shorter distances inside the test chamber. As a result, a much smaller chamber, such as the MA8172A, is used to conduct RF conformance and compliance tests and spurious emissions measurements.  

Figure 4: Comparison of DFF and IFF environments.

As mentioned, the near-field region uses no plane waves and the measurement antenna distorts the measurement results. The small and economical MA8161A shield box is used in this environment to conduct protocol and functional tests.

Creating a Test Environment

The Radio Communication Test Station MT8000A and Radio Communication Analyzer MT8821C are used in OTA test environments to provide core signaling, emulate the RF environment, and implement the protocol stack. Flexible solutions, they support 4G and 5G – both Standalone (SA) and Non-Standalone (NSA). They replicate a live network to create a real-world testing environment in the lab. Furthermore, the instruments meet all the OTA performance and compliance requirements set by various working groups and test plans of the Cellular Telecommunications and Internet Association (CTIA) and major global cellular operators.

Figure 5: Test system to evaluate a mmWave device supporting 2 carrier components on LTE and 2 components in 5G, along with MIMO capability.

Both instruments are part of an integrated 5G NR OTA test system at the Cetecom laboratories in Milpitas, CA. In this configuration (figure 5), the MT8000A and MT8821C are used with the ETS-Lindgren AMS-8600 Antenna Measurement System and EMQuest software to create a comprehensive testing environment.

You can learn more about OTA fundamentals and their importance on 5G NR UE verification by watching this webinar featuring Anritsu and Cetecom.

About the Author:

Keyvan Yasami is a Market Development Manager for Anritsu with 10+ years in the wireless industry. Keyvan holds a Master’s degree in Electrical Engineering from the University of Maine, and a Business Management degree from Harvard University

How Simulation Tools Save Time and Money When Verifying Sensor Performance in V2X Designs

May 4, 2021

Cellular Vehicle-to-Everything (C-V2X) was initially developed to serve as a vehicle communication technology to improve traffic, comfort, efficiency, and safety. Now, it is in the pole position to serve as the technology to lead us to the autonomous vehicle age. To do so, however, simulation and test tools must be developed to efficiently, accurately, and repeatedly conduct measurements on sensors to ensure operation in mission-critical environments.

One reason C-V2X is leading the way is utilization of 5G New Radio (NR). Deployment of 5G NR is enhancing all C-V2X elements – vehicle-to-vehicle (V2V), vehicle-to-pedestrian (V2P), vehicle-to-infrastructure (V2I), and vehicle-to-network (V2N). The high speed and low latency of 5G NR builds a strong foundation for safety use cases, including autonomous vehicles.

C-V2X’s Global Impact

Integration into self-driving vehicles is the logical next step for C-V2X. Various New Car Assessment Programs (NCAPs) around the world are already implementing the communications technology in current connected car use cases. Leading the way is China, as it is committed to a considerable deployment of C-V2X vehicles and infrastructure. Europe is also active, as evident by a new European Standard (EN) positioning C-V2X as an access layer technology for the Intelligent Transportation System (ITS) developed by the European Telecommunication Standardization Institute (ETSI).

Figure 1: C-V2X is a key enabling technology for autonomous vehicles (photo courtesy of dSPACE).

Initial C-V2X deployments in the U.S. are underway, fueled by a recent decision from the Federal Communications Commission (FCC). In November 2020, the FCC adopted new rules that designate the upper 30 MHz (5.895-5.925 GHz) for ITS services and C-V2X as the technology standard for safety-related transportation and vehicular communications. The action by the FCC begins a transition away from Dedicated Short-Range Communications (DSRC) services, thus eliminating one key roadblock in C-V2X becoming the technology of choice for autonomous vehicles.

Autonomous vehicles will utilize emerging communications modes and schemes, such as sidelink and collective perception, respectively. Each leverages C-V2X with 5G NR and integrates multiple sensors, including cameras, radar, and LiDAR. Simulation testing of these sensors are a requirement during design and manufacturing at the device, system, and vehicle levels.

Sidelink and C-V2X

Sidelink, also known as PC5, allows vehicles and roadside units (RSUs) to communicate reliably and directly with each other without the cellular network. To deliver high reliability, C-V2X sidelink relies on blind hybrid automatic repeat request (HARQ), which transmits the same data packet at least twice, each with a different coding. The receiving vehicle reconstructs the original message using both transmitted messages.

3GPP Release 16 5G NR, which includes notifications and maneuvers such as lane changes, outlines the direct communication mode in C-V2X sidelink. 5G NR C-V2X sidelink brings several enhancements, such as higher throughput, lower latency, enhanced reliability, and improved positioning. All are expected to improve autonomous driving. 5G NR C-V2X sidelink also moves the default mode of operation from broadcast to more reliable multicast communication.

Figure 2: 5G NR is aiding in the C-V2X evolution (photo courtesy of Qualcomm).

C-V2X Impact on Collective Perception

Collective perception is especially promising, as it allows connected traffic participants to “see through the eyes of others” by sharing sensor-detected objects via C-V2X. The information exchanged via collective perception allows vehicles to detect objects in their respective Local Environmental Models (LEMs).

Traffic participants and infrastructure use the data collected to inform connected stations of objects, such as pedestrians, obstacles, and other vehicles. The object data are exchanged through Collective Perception Messages (CPM). ETSI is standardizing CPM to ensure its interoperability among all equipped vehicles.

Scenario-based Testing

There are many scenarios, such as number of vehicles and surrounding infrastructure, that need to be properly identified for autonomous vehicles to operate safely. For this reason, verification solutions must conduct scenario-based testing with realistic simulation and 5G network emulation. There must be comprehensive environment simulation with support of trajectory to properly calculate maneuverability.

Device, system, and automotive engineers need to verify that these sensors will operate efficiently before the models reach the road. Utilizing a cellular network simulator provides multiple financial and operational efficiencies compared to conducting the necessary measurements over a live cellular network. Two critical advantages are:

Repeatability – You can’t predict live network performance, but you can with a cellular network simulator. All key parameters – power, channel, data rate, network settings, etc. – can be controlled. The result is repeatable measurements.

Efficiencies – A network simulator allows engineers to emulate real-world scenarios. This creates tremendous cost-of-test and time benefits, as teams don’t have to travel the world conducting measurements on various networks.   

The Anritsu Signalling Tester (Base Station Simulator) MD8475B and Radio Communication Test Station MT8000A are integrated into the dSPACE V2Cloud Solution to create an effective simulation environment. The dSPACE solution provides an integrated development and test environment for data logging and enrichment; machine learning and in-vehicle prototyping; data replay; production software development; scenario generation; and vehicle, environment, and sensor simulation.

One example of the solution’s advantage is conducting measurement-based handovers, an important test for autonomous vehicles. The Anritsu-dSPACE solution can emulate handovers as they are actually done on the live network, as shown in figure 3. The mobile device sends channel quality data reports to the network simulator, which then emulates a threshold for handover. The system makes it easy to simulate complex scenarios, such as roaming and saturation, from anywhere in the world. Handover test cases are built into the GUI to simplify taking measurements and making updates as standards progress.

Figure 3: Network simulators can emulate the complexity of real-world networks such as the one shown here.

You can learn more about conducting C-V2X tests and verification using simulation tools by watching this C-V2X webinar conducted by Anritsu and dSPACE.

Designing for 5G: How Deployment is Changing Priorities

March 24, 2021

The road to 5G has had its speedbumps along the way but the rollout is now at full throttle. With the deployment of 5G New Radio (NR), the realization of the next generation of wireless has led to a fork in the road, if you will. Current 5G implementation is not exactly what was expected a few years back. The reality of 5G has led to different priorities in designing UE, network elements, and the core network itself.

Fierce Wireless had a virtual conference – 5G Blitz Week – to discuss all things 5G. Anritsu was one industry leader to participate. Adnan Khan, Senior Manager – Wireless and Wireline Market Development, participated in a roundtable, during the event.

Also participating was AT&T, whose Senior Vice President of Wireless Technology and Experience Delivery, Igal Elbaz, served as a keynote speaker. During his talk, he stated that 5G is more than a radio access network (RAN) revolution. It’s a core network revolution.

Elbaz’s statement is accurate, as initial use cases are impacting the core network. As articulated by Anritsu Company GM and Vice President Robert E. Johnson in a Q&A session, those use cases are more in the industrial sectors than commercial applications. This view was echoed by speakers at 5G Blitz Week.

Low Latency in Industrial Use Cases

Low latency is a key 5G benefit for industrial applications. Let’s look at a smart factory. There are multiple cameras and AR technology throughout the facility to improve efficiency on the factory floor. This sector needs extensive bandwidth, low latency in the range of <1 ms, as well as multiple connections for reliability with micro- and macro-supported mobility among private/semi-private/public networks for session continuation. In some cases, there will be backup WLAN technology to provide a reliable and robust experience. A mix of low latency and high throughput is necessary to make industrial automation operate according to specification – and expectation – for the appropriate return on investment (ROI).

Mission critical connectivity use cases also need the low latency of 5G, in addition to high levels of reliability and security. One prime example is autonomous vehicles. Typically, four sensor groups form the AV toolkit in an autonomous car. They are video cameras, radar, ultrasonic sensors, and lidar. There must also be a high level of redundancy, requiring overlapping sensors to verify that what a car is detecting is accurate. For all these sensors to operate in the challenges of an automotive environment and in near real-time requires low latency.

Another use case is smart cities, which incorporate elements such as adaptive traffic signals and methods for improved first responder time of arrival. Smart city data is also used to create a digital twin, which helps make communities smarter, safer, and more efficient. City administrators and elected officials create virtual cities based on the data to plan transportation systems, prepare for environmental hazards such as flooding, and even warn citizens about high pollution areas.

Network Design Changes

Given all these use cases – and more to come – it’s no wonder that everyone involved in 5G, from carriers to chip makers, has dissimilar requirements. Every use case has a different network deployment. 5G is very complex and yet configurable at the same time. A variety of advanced features, like Ultra-Reliable Low-Latency Communication (URLLC), make 5G uniquely well positioned to meet all these requirements and capitalize on the market opportunities.

User plane latency is the first target to satisfy the requirements of low latency use cases. User plane latency is the time it takes to successfully deliver an application layer packet or message at the radio protocol layer from the service data unit (SDU) ingress point to the corresponding egress point (TR 38.913). Multi-access Edge Computing (MEC) creates the potential for high processing of large data amounts and a better means to optimize it by having it hosted at the edge of the network and closer to the end user. The goal is to bring the application as close to the user as possible.

From a test perspective, how do we measure latency in this network design? Over-the-Air (OTA) is the answer. Signals need to be measured from the gNodeB to the core network. Subsequently, tests must be conducted from the core network to the edge. Adding to testing complexity is what we refer to as a “data cocktail.” Its ingredients include AI, machine learning, autonomous vehicles, and cellular redirect.

Impact of High Throughput

Many consumer use cases shine a spotlight on high throughput – achieving 2 Gbps. Truthfully, consumers can’t tell the difference at this level of throughput. LTE, with 4x4 MIMO, can achieve 2 Gbps. Operators realize a huge benefit from the switch to 5G, however. 5G is much more efficient. Mobile carriers can send more bits per Hz, thereby using less spectrum. The result is a greater average revenue per user.

Consumer need for throughput is creating a shift from mobility to fixed wireless access. Gateways at the household are providing high throughput benefits, which have become particularly important during the pandemic. It is not uncommon for a parent to be on a business video conference from the home office while one child is enjoying a movie on a streaming service and another is immersing himself/herself in AR gaming.

5G Test Tools

When it comes to selecting the proper 5G test solutions, it’s important that the tools can verify the respective deployment and use case(s). One test instrument does not fit all applications, especially as it pertains to 5G.

For instance, millimeter (mmWave) brings challenges. The physics of mmWaves create considerable propagation loss. It requires OTA tests be made but that can be tricky. The reason is because OTA has propagation properties of its own. Test solutions must compensate for this phenomenon. For this reason, 5G device testing is becoming as complex as network testing.

Another test factor is virtualization and O-RAN, which create their own set of obstacles. Even though it leverages an open interface, engineers must test to ensure the interface is programmed correctly by the manufacturer. Testing must also be done to verify if an interface is compatible with hardware and software from different vendors. A test solution must have the protocol stack specifications properly implemented according to the specifications, as well as hardware that is robust and provides repeatable results. This becomes key when making latency measurements, as a millisecond delta can result in the difference in passing and failing.

Cost-of-test, while a contributing factor in any application, has greater importance with 5G. Many devices have a very low price point, making the cost of the entire design a priority. To meet this requirement, test tools must be built upon a flexible platform that can be easily and affordably expanded as use cases change and specifications evolve.

To learn more about 5G testing and solutions, visit our 5G technology page.