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Overview of 5G System-Level Simulation

Since R2024a

System-level simulation plays a critical role in the design, evaluation, and optimization of the 5G radio access network (RAN). This topic presents these aspects of 5G system-level simulation:

  • Node and network modeling

  • Network scalability

  • Physical layer fidelity

  • Interference modeling

  • System capacity improvement using multi-user (MU) multiple-input multiple-output (MIMO) technology

Node and Network Modelling

Node and network modeling consists of these aspects.

  • Model radio access technologies and antenna configurations — System-level simulation models new radio (NR) base stations (gNBs) and user equipment (UE) nodes. For information on how to create NR nodes, see the nrUE and nrGNB objects. The NR stack of these nodes encompasses radio link control (RLC), medium access control (MAC), and physical (PHY) layers. For further details regarding the NR protocol stack, see Composition of NR Nodes.

    The NR Cell Performance Evaluation with MIMO example demonstrates the modeling of a 5G NR cell featuring a multiple-input multiple-output (MIMO) antenna configuration. This simulation involves a set of UE nodes connected to a gNB node.

  • Node placement — In a 5G network planning scenario, the placement of gNB node is crucial for various reasons, including coverage, capacity, and performance optimization. System-level simulation of 5G enables you to set the positions of the gNB and UE nodes using the Position property of nrUE and nrGNB objects.

  • Model mobility patterns — In system-level simulation, you can model UE movement within the network and study its implications on signal strength and overall network performance. For more information about mobility patterns, see addMobility.

  • Model traffic patterns — In system-level simulation, you can model various application traffic patterns such as file transfer protocol (FTP), On-Off, Video, and voice over Internet protocol (VoIP) traffic models. For example, the Generate and Visualize FTP Application Traffic Pattern example demonstrates the creation of a file transfer protocol (FTP) application traffic pattern. This example showcases the sequence of file transfers with fixed file sizes and variable reading times, offering valuable insights into the characteristics of FTP application traffic models. For more information about traffic models, see the networkTrafficOnOff, networkTrafficFTP, networkTrafficVideoConference, and networkTrafficVoIP objects.

  • Simulate the configured scenario — To simulate the configured network scenario, the system-level simulation uses a wireless network simulator. For more information about this simulator, see Wireless Network Simulator.

For information on how to model, simulate, and evaluate the system-level performance of the 3GPP enhanced mobile broadband (eMBB) indoor hotspot (InH) scenario, see the Evaluate 3GPP Indoor Reference Scenario example.

Network Scalability

Scalability is crucial for 5G networks, as they must support a large number of connected devices while providing high data rates. System-level simulation enables you to create multiple NR nodes in a single object call. For more information about creating multiple NR nodes, see the nrUE and nrGNB objects.

System-level simulation helps you evaluate the scalability of a network by simulating the behavior of a large number of devices and evaluating the impact on network performance. The simulation enables you to analyze factors such as throughput, scheduling fairness, block error rate (BLER), and spectral efficiency under various traffic loads and deployment scenarios.

For example, the NR Interference Modeling with Toroidal Wrap-Around example demonstrates how to model a 19-site cluster containing a total of 57 cells. Each site consists of three collocated gNBs equipped with directional antennas covering 120-degree areas, resulting in 3 sectors per site. This setup provides an opportunity to evaluate network performance in a relatively large-scale deployment scenario.

Interference Modeling

Interference is a significant concern in wireless networks, and 5G is no exception. System-level simulation enables you to accurately model and analyze interference in 5G networks. By considering factors such as neighboring cells and channel conditions, you can evaluate the interference levels and their impact on the network's performance. This information can help you optimize resource allocation, scheduling algorithms, and interference mitigation techniques.

The NR Intercell Interference Modeling example demonstrates the process of simulating a scenario involving interference across multiple cells, and assessing the effects on network performance resulting from downlink (DL) intercell interference generated by neighboring cells.

The example NR Interference Modeling with Toroidal Wrap-Around demonstrates a 19-site cluster setup with toroidal wrap-around, per ITU-R M.2101-0, using the 3GPP TR 38.901 system-level channel model. The wrap-around technique ensures uniform interference across the edge of the cluster by creating a continuous looped environment.

PHY Fidelity Levels

The system-level simulation enables you to simulate two different fidelity levels of the PHY layer: full PHY and link-to-system mapping-based abstracted PHY. Full PHY involves waveform generation and decoding, while abstracted PHY models link quality and performance to calculate the packet error rate. For more information about full PHY and abstracted PHY, see Composition of NR Nodes.

The NR Cell Performance Evaluation with Physical Layer Integration example illustrates the use of full PHY processing. This example simulates a 5G NR cell, which includes a set of UE nodes connected to a gNB node. You can also run the example with a link-to-system mapping-based abstracted PHY layer for expedited runtime performance. For an example that uses a link-to-system mapping-based abstracted PHY layer, see the NR FDD Scheduling Performance Evaluation example.

MU-MIMO

MU-MIMO is a key technique in 5G networks for improving spectral efficiency and increasing system capacity. System-level simulation enables you to evaluate the performance of MU-MIMO by modeling the antenna arrays and channel characteristics of the network.

The NR Cell Performance with Downlink MU-MIMO example demonstrates how to assess the system performance of a codebook-based downlink (DL) MU-MIMO. The example uses a link-to-system mapping-based abstracted physical layer (PHY) to illustrate the evaluation process.

Performance Analysis

By comparing the performance of different network configurations, algorithms, and deployment scenarios, you can gain insight into the behaviour of a system and make informed decisions regarding network design, optimization, and resource allocation. System-level simulation enables you to: