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Overview of 5G System-Level Simulation

Since R2024a

System-level simulation (SLS) aids in the design, evaluation, and optimization of a 5G radio access network (RAN). This topic presents the key 5G SLS functionalities in 5G Toolbox™ and various aspects of 5G SLS modeled using these functionalities.

Key 5G SLS Functionalities

The 5G SLS in 5G Toolbox has these key functionalities.

  • Modeling of data channels and reference signals:

    • Physical downlink shared channel (PDSCH) and physical uplink shared channel (PUSCH)

    • Demodulation reference signal (DM-RS), channel state information reference signal (CSI-RS), and sounding reference signal (SRS)

  • Physical (PHY) layer modelling — Abstracted PHY (link to system mapping) and full PHY

  • Duplex modes — Frequency division duplex (FDD) and time division duplex (TDD)

  • Scheduling strategies — Round-robin (RR), proportional fair (PF), best channel quality indicator (CQI), and custom scheduler

  • Different subcarrier spacing (SCS)

  • Open loop power control

  • Interference modeling

  • Application traffic pattern modeling using file transfer protocol (FTP), On-Off, video, voice over internet protocol (VoIP), and full buffer traffic models

  • Node mobility within a cell by using random waypoint mobility model

  • modulation and coding scheme (MCS), rank, and precoder selection based on measurements performed on the CSI-RS and the SRS

  • Link adaptation

  • Fixed MCS

  • Multiple-input multiple-output (MIMO)

    • Uplink and downlink MIMO

    • CSI Type II based multi-user multiple-input multiple-output (MU-MIMO) with inter-user interference

    • Sounding reference signal (SRS)-based downlink single-user MIMO

  • Hybrid automatic repeat request (HARQ)

  • Medium access control (MAC) logical channel prioritization (LCP)

  • RLC unacknowledged mode (UM) and acknowledged mode (AM)

  • Channel Modeling — Clustered delay line (CDL) channel, 3GPP TR 38.901 system-level channel, and custom channel

  • Key performance indicators — Throughput, block error rate (BLER), and spectral efficiency

  • Ability to gather statistics at the application (APP) layer, radio link control (RLC) layer, MAC layer, and PHY layer.

  • Simulation logs and run-time visualizations

Modeling Various 5G SLS Aspects

You can model these aspects of 5G SLS using the node functionalities.

Node and Network Modeling

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 a cell 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.

    In addition to these traffic models, you can also configure full buffer traffic for a UE node. See the FullBufferTraffic argument of connectUE object function.

  • 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 an example of 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 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 5G SLS 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. Using the SLS, you can analyze factors such as throughput, scheduling fairness, 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.

Resource Scheduling

The role of a scheduler is to efficiently allocate radio resources to UE nodes. The scheduler operates in the MAC layer of the 5G protocol stack. With 5G Toolbox, you can configure an NR scheduler at the gNB node using the configureScheduler object function of the nrGNB object. You can use the Scheduler name-value argument to specify these scheduling strategies.

  • RR scheduler — Provides equal scheduling opportunities to all the UE nodes.

  • Best CQI scheduler — Prioritizes the UE node with the best CQI.

  • PF scheduler — Offers compromise between the round-robin and best CQI schedulers.

  • Custom Scheduler – Allows you to write your custom scheduling logic. To create a custom scheduler, use a subclass inherited from the nrScheduler class. For an example of how to write a custom scheduler, see the Use Custom Scheduler in 5G System-Level Simulation example.

The built-in scheduling strategies RR, best CQI, and PF also perform dynamic link adaptation for both downlink and uplink. To enable link adaptation for downlink, use the LinkAdaptationConfigDL argument of the configureScheduler object function, and for uplink, use the LinkAdaptationConfigUL argument. For a custom scheduler, you can create your own link adaptation algorithm.

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, channel characteristics, and user-pairing in 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 PHY.

You can also perform SRS-based downlink channel Measurements for a TDD System in 5G SLS. Use CSIMeasurementSignalDL of configureScheduler to set the downlink channel measurement signal as SRS. For more information about SRS based downlink channel measurements, see SRS-Based Downlink Channel Measurements for TDD System.

Performance Analysis

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