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802.11 MAC and Application Throughput Measurement

This example shows how to measure the MAC and application layer throughput in a multi-node 802.11a/n/ac/ax network using SimEvents®, Stateflow®, and WLAN Toolbox™. The system-level model presented in this example includes functionalities such as configuring the priority of the traffic at the application layer, capability to generate and decode waveforms of Non-HT, HT-MF, VHT, HE-SU and HE-EXT-SU formats, MPDU aggregation and enabling block acknowledgment of MPDUs. The application layer throughput calculated using this model is validated against published calibration results from the TGax Task Group [ 4 ] for Box 3 scenarios (Tests 1a, 1b, and 2a) specified in TGax evaluation methodology [ 3 ]. The obtained application layer throughput is within the range of minimum and maximum throughput specified in published calibration results [ 4 ].

Throughput in 802.11 Networks

The IEEE® 802.11™ working group is continually adding features to 802.11 specification [ 1 ] to improve the throughput and reliability in WLAN networks. Throughput is the amount of data transmitted over a period of time. Medium Access Control (MAC) layer throughput refers to the amount of data successfully transmitted by the MAC layer over a period of time. MAC protocol data unit (MPDU) is the unit of transmission at MAC layer. In 802.11n, MPDU aggregation was introduced to increase the throughput. When MPDU aggregation is supported, MAC layer aggregates multiple MPDUs into an aggregated MPDU (A-MPDU) for transmission. This reduces the overhead of channel contention for transmitting multiple frames, resulting in enhanced throughput. In 802.11ac [ 1 ] and 802.11ax [ 2 ], the maximum limits for an A-MPDU length were increased resulting in even better throughput in WLAN networks.

Model 802.11 Network

This example models a WLAN network with five nodes as shown in this figure. These nodes implement carrier-sense multiple access with collision avoidance (CSMA/CA) with physical carrier sense and virtual carrier sense. The physical carrier sensing uses the clear channel assessment (CCA) mechanism to determine whether the medium is busy before transmitting. Whereas, the virtual carrier sensing uses the RTS/CTS handshake to prevent the hidden node problem.

The model in the example displays various statistics such as the number of transmitted, received, and dropped packets at PHY and MAC layers. Moreover, the runtime figures that help in analyzing/estimating the node-level and network-level performance are also displayed in this model. This model is validated against the published calibration results from the TGax Task Group [ 4 ] for Box 3 scenarios (Tests 1a, 1b, and 2a) specified in TGax evaluation methodology [ 3 ].

WLAN Network

Components of a WLAN Node

The components of a WLAN node are shown in this figure. The information is retrieved by pressing the arrow button for each node in the above figure.

Application, EDCA MAC and PHY Block Enhancements

This example is an enhancement over Multi-Node 802.11a Network Modeling with PHY and MAC example. Refer to the example documentation page for more information about each layer in a WLAN node. The application, the EDCA MAC and the PHY blocks used in this example has these enhancements over Multi-Node 802.11a Network Modeling with PHY and MAC.


The application layer has the capability to generate data with different priority levels as shown in this figure. These priority levels are configured using Access Category property in the mask parameters of the Application Traffic Generator block inside a WLAN node.


The EDCA MAC block used in this example has these enhancements over MAC block used in Multi-Node 802.11a Network Modeling with PHY and MAC example

  • Generate and decode MAC frames of high efficiency single user (HE-SU), high efficiency extended range single user (HE-EXT-SU), very high throughput (VHT), high throughput mixed format (HT-MF) and Non-HT formats. These formats are configured using the PHY Tx Format property in the mask parameters of the MAC EDCA block inside a WLAN node as shown in this figure.

  • Aggregate MPDUs to form an A-MPDU. This can be configured by setting PHY Tx Format to one of HT-MF, VHT, HE-SU, or HE-EXT-SU. In case of HT-MF, MPDU Aggregation property must also be enabled for A-MPDU generation.

  • Acknowledge multiple MPDUs in an A-MPDU with a single block acknowledgment (BA) frame. MAC assumes a pre-configured BA session between the transmitter and the receiver of an A-MPDU.

  • Enable/disable acknowledgments. This can be configured using the Ack Policy property.

  • Maintain separate retry limits for shorter frames (less than RTS threshold) and longer frames (greater than or equal to RTS threshold). These limits can be configured using the Max Short Retries and Max Long Retries properties.

  • Transmit multiple streams of data using the multiple-input multiple-output (MIMO) capability. You can configure this capability using the Number of Transmit Chains property. This property is applicable only when the value of PHY Tx Format property is set to VHT, HE-SU, or HE-EXT-SU. The MIMO capability can also be used for HT format through the MCS property. The range of values [0, 7], [8, 15], [16, 23], and [24, 31] correspond to one, two, three, and four streams of data respectively.

  • Adapt the data rate according to the channel conditions through the Rate Adaptation Algorithm property. This is applicable only when the value of PHY Tx Format property is set to Non-HT. You can choose between Auto Rate Fallback (ARF) and Minstrel algorithms. To maintain a constant data rate throughout the simulation, Fixed-Rate option is available.

  • Enable parallel transmissions between the basic service sets (BSSs) through the Enable Spatial Reuse with BSS Color property. This property is applicable only when PHY Tx Format property is set to HE-SU, HE-EXT-SU, or HE-MU-OFDMA. This model does not support the spatial reuse (SR) functionality. To study the impact of SR with BSS coloring on the network throughput, refer Spatial Reuse with BSS Coloring in 802.11ax Residential Scenario example.


Capability to generate and decode waveforms of Non-HT, HT-MF, VHT, HE-SU and HE-EXT-SU formats

Throughput Measurement

Throughput varies for different configuration parameters pertaining to the application, MAC & PHY layers. Any change in the configuration may either increase or decrease the throughput. You can vary the combination of these parameters to measure and analyze the throughput.

  • MCS: PHY data rate

  • PHY Tx Format: PHY transmission format

  • Packet Size: Application packet size

  • Max A-MPDU Subframes: Maximum number of subframes in an A-MPDU

  • Max Tx Queue Size: MAC transmission queue size

Along with above parameters, you can also vary the node positions, Tx & Rx gains, channel loss, number of nodes in the network, MAC contention parameters, number of transmit chains and rate adaptation algorithms to analyze MAC throughput. This example demonstrates the measurement and analysis of the MAC throughput by varying packet size in the Application Traffic Generator block.

Application Packet Size

Throughput is directly proportional to the application packet size. Smaller packet size results in greater number of packets to be transmitted. At the MAC layer, there is an overhead of contention time for each transmitted packet. This is because the MAC layer makes sure that the channel is idle for a specific amount of time (Refer section of [ 1 ]) before transmitting any packet. Therefore, as the packet size decreases, the contention overhead increases resulting in lower throughput.

Model Configuration

You can configure the application packet size using these steps:

  1. Open model WLANMACThroughputMeasurementModel.slx

  2. To go inside a node subsystem, click on the downward arrow at the bottom left of the node

  3. To open mask parameters of the application, double click on Application Traffic Generator

  4. To enable application, set App State to 'On'

  5. Configure the value of Packet Size

Run the simulation and observe the throughput. The TGax calibration results for test-1a in [ 4 ] are shown below:

The above plot compares the calibration results for WLAN Toolbox against the published results of other companies listed in [ 4 ]. The blue colored curve represents the results of WLAN Toolbox, while the grey colored curves represent the results of other companies.

Simulation Results

The simulation of the model generates:

  1. A run-time visualization showing the time spent on channel contention, transmission, and reception for each node

  2. An optional run-time visualization (during the simulation) showing the number of frames queued in MAC transmission queues for a selected node.

  3. A bar graph showing metrics for each node such as number of transmitted, received, and dropped packets at PHY and MAC layers

  4. A MAT file statistics.mat with detailed statistics obtained at each layer for each node

This figure shows MAC state transitions with respect to simulation time.

You can also observe the live state of the MAC layer transmission buffers using the 'Observe MAC queue lengths' button in the above visualization.

This figure shows the network statistics at the end of simulation.

Validating Application Layer Throughput with TGax Calibration Results

The TGax Task Group [ 4 ] published application throughput results for different scenarios. You can observe the Layer 3 (above MAC layer) throughput of each node in the network in 'Throughput' column in 'statisticsTable' stored in 'statistics.mat'. The TGax calibration scenarios for MAC simulator published results of application throughput for a User Datagram Protocol (UDP) with Logical Link Control (LLC) layers overhead.

To calculate application throughput from simulation results use the code below:

% Load statistics.mat (Output of the simulation) file
simulationResults = load('statistics', 'statisticsTable');
% Statistics
stats = simulationResults.statisticsTable;

% Successfully transmitted MAC layer bytes in the network
totalMACTxBytes = sum(stats.MACTxBytes);

% UDP & LLC overheads (bytes)
udpOverhead = 36;
llcOverhead = 8;

% UDP & LLC overhead (bytes) in the network
udpAndLLCOverhead = sum(stats.MACTxSuccess)*(udpOverhead + llcOverhead);

% Successfully transmitted application bytes
totalAppTxBytes = totalMACTxBytes - udpAndLLCOverhead;

% Time at which last transmission is completed in the network (Microseconds)
simulationTime = max(stats.MACRecentFrameStatusTimestamp);

% Application throughput (Mbps)
applicationThroughput = (totalAppTxBytes*8)/simulationTime;
disp(['Application Throughput = ' num2str(applicationThroughput) ' Mbps']);
Application Throughput = 4.7276 Mbps

The application throughput for different TGax calibration scenarios is plotted against different MAC service data unit (MSDU) sizes for a simulation time of 30 seconds as shown below:

Further Exploration

Configuration options

You can change these configuration parameters to further explore this example:

  • Application layer: Access category and packet interval

  • MAC layer: RTS threshold, Tx queue size, data rate, short retry limit, long retry limit, transmitting frame format, MPDU aggregation, ack policy, number of transmit chains and the rate adaptation algorithms

  • PHY: PHY Tx gain, PHY Rx gain, and Rx noise figure

  • Channel modeling: Rayleigh fading, free space pathloss, range propagation loss and packet receive range

  • Node positions using node position allocator

  • The state of each node can be visualized during the run-time through the configuration available in the Visualizer block

  • By default, the PHY transmitter and the receiver blocks run in the Interpreted execution mode. For longer simulation time, configure all the blocks to Code generation mode for better performance.

Related examples

Refer these examples for further exploration:

This example enables you to create and configure a multi-node 802.11 network using a Simulink model for analyzing the MAC and application layer throughput. In this model, the MAC throughput obtained through the simulation results is used to calculate the application layer throughput. This model is validated using the Box 3 scenarios (Tests 1a, 1b, and 2a) specified in TGax evaluation methodology [ 3 ] to confirm that it complies with the IEEE 802.11 [ 1 ]. This example concludes that the calculated application layer throughput is within the range of minimum and maximum throughput specified in published calibration results [ 4 ].


The helper functions and objects used in this example are:

  1. edcaFrameFormats.m: Create an enumeration for PHY frame formats.

  2. edcaNodeInfo.m: Return MAC address of a node.

  3. edcaPlotQueueLengths.m: Plot MAC queue lengths in the simulation.

  4. edcaPlotStats.m: Plot MAC state transitions with respect to simulation times.

  5. edcaStats.m: Create an enumeration for simulation statistics.

  6. edcaUpdateStats.m: Update statistics of the simulation.

  7. helperAggregateMPDUs.m: Generate an A-MPDU, by creating and appending the MPDUs containing the MSDUs in the MSDULIST.

  8. helperSubframeBoundaries.m: Return subframes information of an A-MPDU.

  9. phyRx.m: Model PHY operations related to packet reception.

  10. phyTx.m: Model PHY operations related to packet transmission.

  11. edcaApplyFading.m: Apply Rayleigh fading effect on the waveform.

  12. heSIGBUserFieldDecode.m: Decode HE-SIG-B user field.

  13. heCPECorrection.m: Estimate and correct common phase error.

  14. heSIGBCommonFieldDecode.m: Decode HE-SIG-B common field.

  15. heSIGBMergeSubchannels.m: Merge 20MHz HE-SIG-B subchannels.

  16. addMUPadding.m: Add multiuser PSDU padding.

  17. macQueueManagement.m: Create a WLAN MAC queue management object.

  18. roundRobinScheduler.m: Create a round-robin scheduler object.

  19. calculateSubframesCount.m: Return number of subframes to be aggregated.

  20. interpretVHTSIGABitsFailCheck.m: Interprets the bits in VHT-SIG-A field

  21. rateAdaptationARF.m: Create an auto rate fallback (ARF) algorithm object.

  22. rateAdaptationMinstrelNonHT.m: Create a minstrel algorithm object.


  1. IEEE Std 802.11™. "Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications." IEEE Standard for Information technology-Telecommunications and information exchange between systems, Local and metropolitan area networks-Specific requirements.

  2. IEEE P802.11ax™/D4.1. "Amendment 6: Enhancements for High Efficiency WLAN.." Draft Standard for Information technology - Telecommunications and information exchange between systems Local and metropolitan area networks - Specific requirements -Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications.

  3. IEEE 802.11-14/0571r12. "11ax Evaluation Methodology." IEEE P802.11P: Wireless LANs.

  4. Baron, Stephane., Nezou, Patrice., Guignard, Romain., and Viger, Pascal. "MAC Calibration Results." Presentation at the IEEE P802.11 - Task Group AX, September 2015.

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