Private 5G networks are becoming fundamental to enterprises

By Avnet Staff   |   January 27, 2023   |   Provided By Avnet Silica

Avnet has partnered with Otava and Rohde & Schwarz to develop a 5G RF virtual evaluation kit

5G is not just about your cell phone. 5G delivers improvements to every type of user. As part of its design, 5G deals with how all kinds of devices will interact and even share control over wireless connections. Private 5G networks are a fundamental part of this new generation.

How 5G supports private cellular networks

Improvements in the core 5G standards deal with latency and guaranteed data-delivery. This enables new applications. Robots can cooperate on a factory floor, live, without a wired network. 5G is intended for real-time control as well as passing IoT data. Further changes lie in 5G's support for private networks. Not everyone needs to use public 5G networks for business-critical systems. Private networks with additional features are tuned to their needs using the same core protocols.

The 5G protocol set by 3GPP has key elements to support private networks. The additions include time-sensitive networking (TSN) and mobile edge computing (MEC). TSN was already supported by Ethernet for automotive, industrial and real-time multimedia delivery. TSN guarantees delivery times and prioritizes network access to high-criticality data. Recent releases of the 3GPP standards provide this capability for 5G wireless. MEC can be important for both privacy and latency. MEC ensures traffic stays within a set of local nodes instead of being relayed to a centralized core and back again.

How mmWave differs from sub-6GHz networks

The 5G framework enables much higher data rates within a cell. 5G provides access to bands in the millimeter-wave (mmWave) spectrum above 10 GHz. A major advantage of the mmWave is that it avoids the sub-6 GHz congested spectrum used to carry consumer data traffic. It also provides access to much wider frequency bands to carry more data per channel.

How MIMO antennas enable beamforming

The higher frequencies used in mmWave are directional. This makes them good for private, on-campus or indoor use. At these frequencies, wave propagation is mostly confined along a preferred direction from the antenna. The signal will be highly attenuated the farther away the receiver is from the axis of propagation. As with radar and similar systems, the waves are highly amenable to electronic beamforming.

An antenna does not need to be turned physically to change the preferred direction of propagation. The combination of multiple antennas and digital signal processing (DSP) makes it possible to apply constructive and destructive interference to a group of parallel antennas. The result is the ability to rotate the preferred direction of wave propagation electronically.

The evolution of cellular networks to use multiple-input, multiple-output (MIMO) antenna configurations has helped deliver efficient mechanisms for beamforming. In turn, that supports the creation of more effective, high coverage mmWave networks.

MIMO began to be used heavily in cellular during the rollout of the 4G LTE networks. The key reason for using MIMO in 4G was to support spatial multiplexing. Multiple users could use the same sub-bands in the cell’s area without interfering with each other. In doing so, MIMO increased the capacity and aggregate data rate for a single base station.

The same architecture can support beamforming with the addition of more antennas beyond the four or eight often deployed to support spatial multiplexing. These massive MIMO configurations may use as many as 64 antennas to support beamforming not just horizontally but vertically. This could enable beams to target users or devices on a floor of a high building or warehouse.

The fundamentals of beamforming are explained here and in more technical detail here.

Thanks to beamforming, it becomes possible to maintain high data rate communications with moving devices in a factory, warehouse or campus. Fixed machinery can operate without wires. Companies avoid the cost and disruption caused by installing network cables.

Automated guided vehicles can maintain constant contact with a server as they move around. There is no need for complex cable supports for robots. This makes it easier to move, rotate and extend when working on a production line.

The combination of mmWave transmission and massive MIMO in a private-network environment enables sophisticated systems of systems. But implementation can be complex. Maintaining a reliable link with a moving target involves a high degree of coordination between the base station transceiver and the end device. This is far more sophisticated than the technology used in 4G systems.

How standards have evolved for 5G beam management

In the older LTE environment, user equipment (UE) periodically measures the quality of the radio signal provided by the base station (eNodeB). The eNodeB uses that data to determine whether the network can support the UE with an acceptable level of link quality. If the link quality falls below a threshold, it triggers a cell re-selection procedure. Reconnection leads to a temporary loss of telemetry, which is unacceptable in real-time control scenarios.

To solve the problem, the 3GPP standards body defined two main types of active beam-management procedures. One is for situations where there are no active communications between the UE and the eNodeB, which is also used when the UE connects for the first time to a given cell. This involves beam sweeping. The eNodeB asks the UE to identify which of the beams is providing the best signal quality. The UE provides measurements that help the eNodeB better support the UE.

Connected mode provides a low-latency mechanism for continually altering signal characteristics while the UE moves around within the cell. This continuous adjustment prevents the signal from deteriorating to the point where a link needs to be re-established.

Beam management operates at both the physical and media access control (MAC) layers. It allows the beam direction to be optimized dynamically as a target moves. If the UE moves far enough within the cell, the system’s algorithms may consider transferring to a neighboring cell.

The 3GPP standards provide the basis for beam management. Delivering active beam management will be implementation dependent. The environment may contain large obstructions that cause strong reflections. An example would be stacks of products in a warehouse. Heavy industrial operations could generate interference. Algorithms developed for public networks to support non-real-time traffic may not be appropriate for private Industry 4.0 networks.

Why 5G networks rely on software defined radio

Software defined radio (SDR) provides the ability to tune systems to different environments without demanding changes to the underlying hardware platforms. Published experiments have shown that SDRs have the real-time performance needed to support massive MIMO beamforming mmWave transmission frequencies. SDR further provides the implementor with access to standards-based open-source software designed to support 5G networks.

Hardware evaluations using open-source infrastructure is now possible and can streamline the path to final production. Target environments may favor certain types of beam configuration and scanning over others. It may even be beneficial to build in adaptation algorithms that work hand-in-hand with site surveys during deployment to achieve optimal results. That calls for flexible hardware that can be fully controlled by software.

How a mmWave toolkit accelerates 5G network design and simulation

SDR reduces the dependence on the hardware platform. Defining through software maximizes flexibility. But implementing 5G mmWave still relies on high-quality hardware to support physical-layer processing and transmission.

Avnet, in association with several key vendors, has assembled a toolkit that supports the development and rapid prototyping of beamforming-capable mmWave 5G hardware. The tools cover:

• Simulation and evaluation of different beamforming techniques
• Adaption algorithms for different scenarios
• Hardware that supports lab and field-based testing

The evaluation phase puts the technology into a live environment. The Avnet evaluation kit is based on several key components:

• A single-chip beamformer with control solution
• A high-performance field-programmable gate array
• An embedded multicore SoC

The kit was developed in cooperation with test-and-measurement specialist Rohde & Schwarz.

The evaluation kit includes Otava’s OTBF103-EVAL beamformer evaluation board and a MicroZed-based digital controller that incorporates Xilinx’s Zynq-7000 SoC. The hardware is supported by a GUI-based Windows application that provides easy access to the control registers for the Otava beamformer IC, handled by the MicroZed controller board. High-grade Samtec connectors ensure high quality for the analog signals that pass through to the MIMO antenna. The GUI generates the digital controller code. The kit can be controlled from a PC through a standard USB or Ethernet connection.

The ability to quickly program the Otava beamformer to handle different scenarios and test setups makes it easier to understand how the settings and the RF environment interact. By running higher-level traffic over the wireless links, developers can experiment with moving UEs running real-time software to see how well the physical-layer beamforming algorithms can adapt to rapid changes in position and the reflections found in a typical target use case.

A further component that is important for evaluation and development is the antenna module itself. In Avnet’s solution, this support is provided by the Fujikura FutureAccess Phased-Array Antenna Module (PAAM), which has been incorporated into Avnet’s development platform in combination with a real-time SDR core. Key features include:

• An 8 x 8 antenna array
• Operation from 24 GHz to 30 GHz
• Support for beam steering of up to ±60 degrees in both horizontal and vertical directions

Armed with the data collected from the evaluation, developers can choose to proceed with a design that builds on their experience to both optimize the physical-layer transmission characteristics and the MAC-level protocol processing that will be required to support real-time applications. An important element of that R&D is software-based simulation.

Using tools such as Matlab and Simulink from The MathWorks, developers can work in the virtual domain to collect data while evaluating different algorithms and control strategies. They can then move on to hardware implementation, using the results to fine-tune the algorithms and settings.

How private 5G networks can democratize cellular communications

The ability to evaluate an RF setup quickly and easily, even one as complex as a private 5G network, is essential to delivering high-quality systems in a timely fashion. The combination of simulation using Matlab and similar tools with hardware-based tools is readily enabled by the Avnet evaluation and development platform for 5G mmWave MIMO.

With these tools, OEMs and integrators can confidently build transceivers and other supporting equipment for 5G. Private networks will be used to help deliver Industry 4.0 and other innovations in enterprise-level systems. Cellular networks are no longer the exclusive domain of traditional telecom operators.

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