Overview of WLAN System-Level Simulation

R2026b

Since R2026b

System-level simulation (SLS) aids in the design, evaluation, and optimization of a wireless local area network (WLAN). This topic presents:

• Key WLAN SLS functionalities in WLAN Toolbox™

• Aspects of WLAN SLS modeled using these functionalities

• Factors that affect simulation execution time

Key WLAN SLS Functionalities

The WLAN SLS in WLAN Toolbox provides these key functionalities.

• IEEE® 802.11™ functionalities include:

  • Enhanced distributed channel access (EDCA) and quality of service (QoS)

  • Support for the 20 MHz, 40 MHz, 80 MHz, 160 MHz, and 320 MHz channel bandwidths

  • Support for the MAC protocol data unit (MPDU), aggregated MPDU (AMPDU), beacon, request to send (RTS), clear to send (CTS), acknowledgement (ACK), block ACK (BA), multi-STA BA, and trigger frames including basic trigger frame, multi-user-RTS (MU-RTS), MU-block ACK request (MU-BAR) frames

  • 802.11ax™ (Wi-Fi^® 6) uplink (UL) and downlink (DL) orthogonal frequency-division multiple access (OFDMA) with abstracted PHY

  • Overlapping basic service set (BSS) packet detect (OBSS PD) based spatial reuse with BSS coloring

  • 802.11be™ (Wi-Fi 7) simultaneous transmission and reception (STR) and enhanced multi-link single-radio (EMLSR) modes of multilink operation (MLO)

  • Dynamic bandwidth channel access (DBCA) support

  • Support for 2.4 GHz, 5 GHz, and 6 GHz multiband operation

  • Wi-Fi mesh network, including hybrid mesh

  • 802.11bn™ (Wi-Fi 8) coordinated time division multiple access (Co‑TDMA) multi-access point coordination (MAPC)

• Abstracted PHY or full PHY modeling

• Interference modeling

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

• Node mobility

• Support for running multiple independent simulations in parallel by using perfor.

• Logging, visualizing, and analyzing network behavior

• Support for simulating Wi-Fi networks in a graphical user interface

Modeling WLAN System-Level Simulation

WLAN system-level simulation supports modeling key aspects of Wi-Fi networks, including node and network configurations, channel effects, rate control, PHY and MAC abstractions, interference, and coexistence. Together, these capabilities enable system-level performance evaluation across a wide range of deployment scenarios.

Node and Network Modeling

Node and network modeling consists of these aspects.

• Model infrastructure BSS — A BSS models a standard Wi-Fi network where one Access Point (AP) serves a set of associated Stations (STAs). Use these function to model a BSS:

  • wlanNode — Represents a node in the network (AP or STA)

  • wlanDeviceConfig — Sets the role of a node by using the Mode property ("AP" or "STA") and configures its MAC and PHY parameters

  • associateStations — Associates one or more STA nodes to an AP node, forming the BSS

• Multi-link Operation (MLO) — MLO allows a multi-link device (MLD) to leverage multiple radio links to improve reliability. Use these functions to implement MLO:

  • wlanLinkConfig — Configures MAC and PHY layer settings for a link

  • wlanMultilinkDeviceConfig — Configures the MLD role ("AP" or "STA") and the MLO mode:

    • Simultaneous transmit and receive (STR ) — The device transmits and receives across all links at the same time

    • Enhanced multi-link single Radio (EMLSR) — The device activates one radio at a time while aggregating across links

  • wlanNode — Hosts the multilink device configuration and operates across the assigned links

  • associateStations — Links STA MLDs to an AP MLD and maps each STA link to a corresponding AP link

  For examples of how to simulate MLO, see the 802.11be System-Level Simulation Using STR Multi-Link Operation and 802.11be System-Level Simulation Using EMLSR Multilink Operation examples.

• Co-TDMA — Co-TDMA is a technique that enables multiple APs to coordinate their transmissions, which reduces channel access delay and can improve worst-case latency. Use the establishMAPCAgreement object function of the wlanNode object.

• Modeling nodes with mixed WLAN standards — WLAN SLS enables you to create networks that contain nodes of different Wi-Fi generations. Use the StandardCapability property of the wlanDeviceConfig and wlanMultilinkDeviceConfig objects to specify the WLAN standard for the device operation.

• Multi-band Operation — Multi-band operation lets nodes transmit and receive across different frequency bands. Use these functions:

  • wlanDeviceConfig — Sets the operating band and channel of a node by using the BandAndChannel property

  • wlanNode — Creates a multi-band AP by accepting a vector of wlanDeviceConfig objects, each configured on a different band, enabling the AP to serve stations across multiple frequency bands simultaneously

  • associateStations — Associates stations operating on different bands to the same multi-band AP

  For an example of how to simulate a multi-band operation, see Simulate Multiband 802.11ax Network.

• Model mesh and Hybrid Mesh Networks — A mesh network enables multi-hop communication between mesh nodes by forwarding traffic through intermediate relay nodes. Use these functions to create mesh and hybrid mesh topologies:

  • wlanNode — Represents each mesh node in the network

  • wlanDeviceConfig — Assigns the mesh role to a node by using the Mode property

  • addMeshPath — Defines a forwarding path between source and destination nodes, either directly or through intermediate mesh nodes for multi-hop communication

  For an example of how to create a mesh network, see the Create, Configure, and Simulate 802.11ax Mesh Network example.

  For hybrid mesh networks, a single wlanNode node can contain multiple wlanDeviceConfig objects with different modes, such as "AP" and "mesh". This configuration enables the node to simultaneously provide infrastructure access to associated STAs and participate in mesh backhaul forwarding. For example, the AP interface can serve associated stations in one band while the mesh interface forwards traffic between mesh nodes in another band.

  For an example of how to create a hybrid mesh network, see the Simulate 802.11ax Hybrid Mesh Network example.

• Model mobility patterns — In system-level simulation, you can model the node movement and study its implications on signal strength and overall network performance. You can configure built-in mobility models such as random walk, random waypoint, and constant velocity. For more information about mobility models, see nodeMobilityRandomWalk (Wireless Network Toolbox), nodeMobilityRandomWaypoint (Wireless Network Toolbox), and nodeMobilityConstantVelocity (Wireless Network Toolbox). You can also create a custom mobility model by using the wnet.Mobility (Wireless Network Toolbox) class.

• 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 more information about traffic models, see networkTrafficOnOff (Wireless Network Toolbox), networkTrafficFTP (Wireless Network Toolbox), networkTrafficVideoConference (Wireless Network Toolbox), and networkTrafficVoIP (Wireless Network Toolbox). You can also create a custom traffic model by using the wnet.Traffic (Wireless Network Toolbox) class. In addition to these traffic models, you can also configure full buffer traffic for WLAN nodes. To configure full buffer traffic, use the FullBufferTraffic argument of the associateStations object function.

Channel Modeling

You can model the following channel effects in WLAN SLS:

• Fading — Models multipath fading by using the IEEE 802.11ax (TGax) channel model with the Model-D delay profile under non-line-of-sight (NLOS) conditions.

• Path loss — Supports free-space, residential, and custom (user-defined) path loss models.

You can plug the channel into the simulation by using the addChannelModel (Wireless Network Toolbox) object function of the wirelessNetworkSimulator (Wireless Network Toolbox) object. For an example of how to plug a channel into the system-level simulation, see the Get Started with WLAN System-Level Simulation in MATLAB example.

Rate Control

Rate control dynamically adjusts the modulation and coding scheme (MCS) and number of space-time streams per transmission based on link quality. Use these functions to configure rate control:

• wlanDeviceConfig — Sets the rate control algorithm for non-MLD nodes by using the RateControl property.

• wlanLinkConfig — Sets the rate control algorithm for MLD nodes on a per-link basis by using the RateControl property.

• wlanRateControlARF— Implements the auto rate fallback algorithm, which automatically increases or decreases the MCS based on transmission success and failure counts.

• wlanRateControl — Serves as the base class for building a custom rate-control algorithm.

Physical Layer Modeling

In system-level simulation, you can model a full physical (PHY) layer or an abstracted PHY layer. The PHYModel property of the wlanNode object enables you to choose between full PHY processing and a statistical abstraction.

Full PHY involves waveform generation and decoding, while abstracted PHY models link quality and performance to calculate the packet error rate. WLAN Toolbox supports two PHY abstraction models:

• MAC Calibration — This simple PHY abstraction model targets MAC-focused simulations. It uses interference to determine whether a node successfully receives a packet. If interference is present at any point in the packet duration, the model considers the reception of the signal of interest unsuccessful. Otherwise, it treats the packet reception successful.

• TGax Evaluation Methodology — This PHY abstraction model determines whether a node successfully receives a packet by accounting for the channel model, the transmission scheme, and interference.

Modeling the PHY in this way for large networks is computationally expensive. For faster simulation, you can use the abstracted PHY. However, this model relies on certain assumptions. For more information about these assumptions, see PHY Modeling Assumptions and Limitations.

For more information about physical layer abstraction in the system-level simulation, see the Physical Layer Abstraction for System-Level Simulation example. For an example of how to simulate a Wi-Fi network in a residential scenario, see the 802.11ax Multinode System-Level Simulation of Residential Scenario example.

MAC Frame Abstraction

The MACModel property of the wlanNode object enables you to choose between full MAC frame generation and decoding or a frame-abstraction mode that passes frame information as a structure instead of actual MAC frame bits. Both modes perform the same MAC operations.

Interference Modeling

Interference modeling controls how a node accounts for signals from neighboring nodes operating on the same or adjacent channels. Use these functionalities to configure interference:

• wlanDeviceConfig — Sets the interference modeling type for non-MLD nodes by using the InterferenceModeling property, choosing between co-channel, overlapping adjacent channel, or non-overlapping adjacent channel interference

• wlanLinkConfig — Sets the same for MLD nodes on a per-link basis

Coexistence Modeling

Coexistence modeling represents how multiple wireless networks operate in the same frequency band. You can model coexistence between heterogeneous networks such as WLAN and Bluetooth. For examples of coexistence simulations, see these examples:

• Explore Bluetooth LE and WLAN Coexistence in 6 GHz with LBT

• Collaborative Coexistence of WLAN, Bluetooth LE, and BR/EDR Using PHY Packet Traffic Arbitration

• Simulate Noncollaborative Coexistence of WLAN, Bluetooth LE, and Bluetooth BR/EDR Networks

Simulate Configured Wi-Fi Network

You can simulate the configured Wi-Fi network scenario by using the wirelessNetworkSimulator (Wireless Network Toolbox) object. For more information about this simulator, see Wireless Network Simulator (Wireless Network Toolbox).

Alternatively, for the simulation of WLAN network scenarios, you can use the Wireless Network Modeler (Wireless Network Toolbox) app. For an example of app-based simulation of a Wi-Fi network, see Model and Analyze WLAN Network Using Wireless Network Modeler App.

Log, Visualize, and Analyze Network Behavior

You can get insight on the behavior of a system by comparing the performance of different network configurations, algorithms, and deployment scenarios. You can:

• Evaluate key performance indicators (KPIs) such as throughput, packet loss ratio, and latency.

• Retrieve various statistics captured at different layers of a node by using the statistics function.

• View packet communication in the simulated network over time and frequency domains by using the wirelessTrafficViewer (Wireless Network Toolbox) object. It shows how nodes transition through different states to exchange packets over time and the portion of the spectrum occupied by each packet.

• View the nodes in the wireless network along with their mobility by using the wirelessNetworkViewer (Wireless Network Toolbox) object.

• Log captured protocol packets into a PCAP or PCAPNG file by using the wlanPCAPWriter object.

• Log network events, such as packet transmissions and receptions for later analysis of node behavior, by using the wirelessNetworkEventTracer (Wireless Network Toolbox) object.

• Capture IQ samples of the composite signal received at a node, including interference effects, for detailed signal analysis by using the wirelessIQLogger (Wireless Network Toolbox) object.

Factors Affecting Simulation Execution Time

Simulation execution time depends on modeling choices and configuration parameters.

Network Size and Topology

The scale of the simulation depends on the number of BSSs, the number of STAs per BSS, and the network density. Larger networks increase the number of interactions and simulation events.

Packet Transmission Characteristics

Short packet transmission times increase the number of events, which increases execution time. Transmission time depends on factors such as the PHY transmission format, aggregation limit, MCS, bandwidth, the number of spatial streams, OFDMA configuration.

Channel Modeling Complexity

Detailed fading models increase computation.

PHY and MAC Fidelity

The choice of PHY and MAC model impacts the runtime of system-level simulations. Enabling full PHY processing also increases simulation execution time. Similarly, enabling full MAC frame generation and decoding increases simulation execution time.

Enabling Visualization

Enabling packet visualization adds runtime overhead.

PCAP Logging and IQ Sample Capturing

Logging MAC protocol data units (PDUs) into a PCAP file for each packet transmission increases simulation time, particularly as the number of nodes increases. Similarly, periodically capturing IQ samples from nodes adds to the computational load.