This example models a multi-node Bluetooth mesh network discrete event simulation (DES) by using the Communications Toolbox™ Library for the Bluetooth® Protocol. DES is the process of simulating the behavior of a system as an ordered and discrete sequence of well-defined events occurring in the time domain. DES allows you to model events in a system that occur in microsecond granularity. Moreover, DES also results in low simulation time thus making it viable to support large-scale system-level simulations. The multi-node mesh network simulated in this example models the complete Bluetooth mesh stack over the advertising bearer. The example aims to accurately model the asynchronous transmissions by using DES. The simulation results include packet delivery ratio (PDR), node-related statistics, and a plot displaying the visual representation of the mesh network.
The Bluetooth Core Specification [ 1 ] includes a low energy version for low-rate wireless personal area networks, referred as Bluetooth low energy (BLE) or Bluetooth Smart. The BLE stack consists of the: generic attribute profile (GATT), attribute protocol (ATT), security manager protocol (SMP), logical link control and adaptation protocol (L2CAP), link layer (LL) and physical layer (PHY). BLE was added to the standard for low energy devices generating small amounts of data, such as the notification alerts used in applications like home automation, healthcare, fitness, and the Internet of Things (IoT).
The Bluetooth Mesh Profile [ 2 ] defines the fundamental requirements to implement mesh networking solutions for BLE. The mesh stack is located on top of the Bluetooth Core Specification and consists of the: model layer, foundation model layer, access layer, upper transport layer, lower transport layer, network layer and bearer layer. Bluetooth mesh networking enables end-to-end communication in large-scale networks to support applications like smart lighting, industrial automation, sensor networking, asset tracking, and many other IoT solutions.
This figure shows the Bluetooth mesh stack over the advertising bearer.
Model layer: This layer defines the models, messages, and states required to create user scenarios. For example, to change the state of a light to On or Off, use the 'Generic onOff set' message from the 'Generic onOff' model.
Foundation model layer: This layer defines the models, messages, and states required to configure and manage the mesh network. This layer configures the element, the publish and the subscription addresses of the node.
Access layer: This layer defines the interface to the upper transport layer and the format of the application data. This layer also controls the encryption and decryption of the application data in the upper transport layer.
Upper transport layer: The functionality of the upper transport layer includes encryption, decryption and authentication of the application data and provides confidentiality of the access messages. This layer also generates the transport control messages (Friendship and Heartbeat) and transmits them to the peer upper transport layer.
Lower transport layer: The functionality of lower transport layer includes segmentation and reassembly of upper transport layer messages into multiple lower transport layer messages. This layer helps to deliver large upper transport layer messages to other nodes in the network. It also defines the Friend queue used by the Friend node to store the lower transport layer messages for a Low Power node.
Network layer: This layer defines encryption, decryption, and authentication of the lower transport layer messages. It transmits the lower transport layer messages over the bearer layer and relays the mesh messages when the 'Relay' feature is enabled. It also defines the message cache containing all the recently seen network messages. If the received message is in the cache, then it is discarded. The message cache is used by the relay nodes (nodes in which the 'Relay' feature is enabled).
Bearer layer: This layer is an interface between the Bluetooth mesh stack and the BLE core stack. This layer is also responsible for creating a mesh network by provisioning the devices. Here, provisioning implies authenticating and providing basic information to a device. A device must be provisioned to become a node. This example assumes all the nodes are already provisioned into a mesh network. The two types of bearers supported by the Bluetooth mesh are advertising bearer and GATT bearer. This example uses only the advertising bearer.
BLE Core Stack
This example models these layers of the BLE core stack:
Generic access profile: This profile defines advertising data (AD) types for carrying mesh messages over the advertising bearer. This example supports 'Mesh message' AD type, which is used for exchanging network layer messages between mesh nodes.
Link layer: This layer defines Broadcaster and Observer roles for message exchange between the nodes within the Bluetooth mesh network. In a Broadcaster role, a node always advertises. Whereas in an Observer role, the node always scans for the advertisers. Each node in the mesh network switches between these two roles to serve as a Bluetooth mesh node.
Physical layer: This layer transmits and receives the waveforms for exchanging messages between the nodes within the Bluetooth mesh network. This layer models channel impairments such as free-space path loss, range propagation loss, and interference.
DES is a type of simulation that models the functioning of a system as a discrete sequence of events in the time domain. Each event occurs at a specific time epoch and subsequently marks a change of state in the system. As a result, the simulation can directly jump from event to event in the time domain. The fundamental advantages of using DES in this example are:
Its flexibility in time handling to suppress or expand, allowing the simulation to speed-up or slow-down the phenomena under investigation. This property of DES is used to model asynchronous transmissions in a multi-node Bluetooth network, resulting in accurate modeling of collisions.
DES improves the simulation time performance and thus makes it feasible to support large-scale system-level simulations. For accurate modeling in a MATLAB implementation, simulations might need to run in microsecond steps. This will not only increase the simulation time but will also impact the network scalability. An increase in the step time might not allow you to capture or schedule events that occur in the microsecond granularity. DES enables you to address this issue by modeling events in discrete points in time.
% Check if the 'Communications Toolbox Library for the Bluetooth Protocol' % support package is installed or not. commSupportPackageCheck('BLUETOOTH');
This example models a Bluetooth mesh network with 21 nodes. The model outputs PDR of the network along with different statistics such as the number of transmitted, received, and dropped packets at physical, link, and network layers, and also a plot visualizing the network scenario. The modeling includes:
Multiple nodes, where each node contains a Bluetooth mesh packet generator and receiver (mesh packet includes model, access, and transport layer encoding and decoding), network layer, link layer, and physical layer
A shared channel, which is simulated with these channel impairment options: range propagation loss, free-space path loss, and interference
Packets transmitted over the shared channel
A node position allocator (NPA) that configures the position of nodes in the network. NPA supports linear, grid, and list allocation strategies
A visualizer that visualizes the mesh network scenario
To configure a specific scenario, do one of these:
Update the default configuration parameters for each node in the preceding model
Specify the configuration as an input to helperBLEMeshCreateNetworkModel for creating a mesh network model
Each node is modeled as a subsystem with a network stack, which includes the Bluetooth mesh packet generator and receiver, network layer, LL, and PHY.
The application layer is implemented to generate and receive application traffic. It is divided into two sub-blocks:
Bluetooth mesh packet generator This block uses the SimEvents Entity Generator block to generate lower transport data protocol data unit (PDU). The generated PDU contains the model layer message of type 'Generic onOff set unacknowledged' appended with higher layer headers. This PDU is passed to the network layer. You can configure the application state (On/Off), name of the destination node, source rate (in packets/second), and maximum number of packets that can be transmitted from source to destination by using this block. The block stops generating the packets once it has generated the maximum number of packets configured.
Bluetooth mesh packet receiver This block uses the SimEvents Entity Terminator block to receive the output from the network layer
The network layer is modeled as a DES block. This block is responsible for transmitting the lower transport layer messages over the advertising bearer and relaying the mesh messages when the 'Relay' feature is enabled. When a network PDU is received, this block decodes the received PDU. If the PDU is decoded successfully, then the decoded information is passed to the lower transport layer.
You can configure the relay feature, network transmit interval, network transmit count, relay retransmit interval, and relay retransmit count by using mask parameters of the Network layer block.
The link layer is modeled as a DES block. This block maintains a state machine for LL Broadcaster and Observer roles. This block is responsible for transmitting and receiving the mesh advertising packets by using
You can configure scan and advertising intervals by using mask parameters of the Link layer block.
The PHY functionality includes:
LL initiates packet transmission by sending an LL packet and Tx indication to the PHY Tx block. This block generates a waveform for the received LL packet by using the
bleWaveformGenerator function. It also scales the samples of the BLE waveform with the configured Tx power (assuming Tx gain is 0). The generated BLE waveform is transmitted through the shared channel. The shared channel is modeled by using the SimEvents Multicast Queue.
You can configure the Tx power (dBm) by using mask parameters of the PHY Tx block.
Channel impairments modeling
The free-space path loss model is added to the transmitted BLE waveform as channel impairments. You can choose to enable or disable this impairment. In addition to this impairment model, the signal reception range can also be limited by using an optional range propagation loss model. To model any of these channel impairment options, the channel model must contain the position of both the sender and the receiver. The channel is modeled inside each receiving node, before passing the BLE waveform to the PHY Rx block.
You can configure channel impairments by using mask parameters of the BLE channel block.
This block applies thermal noise and interference to the received BLE waveform (assuming Rx gain is 0). Thermal noise is modeled by using the
comm.ThermalNoise function with the configured value of the noise figure. Interference is modeled by adding the IQ samples of both the interfered and the actual signals. After applying thermal noise and interference, PHY Rx block decodes the resultant waveform. If the LL packet is decoded successfully, then it is passed to the LL.
You can configure the noise figure (in dB) using mask parameters of the PHY Rx block.
Node position allocator (NPA) Assigns the location of nodes in the mesh network. This block supports linear, grid, and list position allocation strategies.
Linear position allocation Places nodes uniformly in a straight line on a 2D grid
Grid position allocation Places nodes in a grid format specified by the grid properties
List position allocation Assigns node positions from a list [[x1, y1, z1] [x2, y2, z2] ... [xn, yn, zn]] such that (xk, yk, zk) is the position of the kth node for all k in (1, 2, ..., n)
Visualizer This block is used to visualize the mesh network scenario in the simulation. You can configure this block to visualize the specified configuration. You can enable or disable visualization by using the mask parameters of this block.
The results obtained in this simulation are:
Packet delivery ratio (PDR)
The PDR is the ratio of number of received packets at the destination to the number of packets transmitted by the source and is given by:
This model outputs PDR for this multi-node mesh network and is saved to a base workspace variable named
Statistics at each node
This model outputs statistics of each node in the workspace variable
statisticsAtEachNode. The statistics captured at each node are:
Number of transmitted and received messages at the PHY
Number of transmitted and received messages at the LL
Number of messages received with CRC failures
Number of transmitted, received, and dropped messages at the network layer
Number of messages relayed at the network layer
Number of received application messages at the network layer
A plot with visual representation of the mesh network scenario is shown in the simulation. You can see the statistics of each node by placing your cursor over it.
This example shows how to configure and simulate a multi-node Bluetooth mesh network by using DES. The mesh network model in this example outputs PDR as a workspace variable with a visual representation of the mesh network.
To observe the variation in the network PDR, you can vary the configuration parameters at the mesh packet generator, the network layer, LL and PHY. In these simulation results, you can see the impact of network layer repetitions (NLR) on the network PDR.
The NLR includes the repetitions of both the network messages and the relayed messages. The working principle of flood-based networks ensures that the message reaches the destination node. Therefore, it is important to retransmit the network and the relay messages. The number of NLR is dependent on the network configuration of the given network topology. Increasing the number of NLR ensures that the likelihood of the messages reaching the desired destination node is high. However, specifying a high value of the NLR can have adverse effects on the network performance parameters such as the overhead, energy consumption, and the duty cycle. As a result, it is essential to tune the value of NLR for a given network topology and achieve an efficient tradeoff between the PDR and network performance.
In the preceding figure you can see that the PDR increases with the NLR and decreases with the number of source nodes in the network. For a specific value of the NLR, the PDR value reaches 1 and thereafter it stabilizes. This specific value of the NLR might vary based on the network configuration parameters such as the total number of nodes, location of the nodes, number of source nodes, number of relay nodes, and so on. You can run helperBLEMeshDESPDRCalculation to reproduce these results by using three source nodes. Set the number of source nodes to two and five to get the corresponding results. You can run the simulations for any custom network scenario and get the optimal value of the NLR.
Apart from the NLR, the PDR varies with respect to multiple configuration parameters stated in helperBLEMeshDESPDRCalculation. You can further explore the mesh network model by varying any of these parameters.
The example uses these features:
bleLLAdvertisingChannelPDUConfig: Create a configuration object for the BLE Link Layer advertising channel PDU
bleLLAdvertisingChannelPDU: Generate BLE Link Layer advertising channel PDU
bleLLAdvertisingChannelPDUDecode: Decode BLE Link Layer advertising channel PDU
bleWaveformGenerator: Generate BLE waveform
The example uses these helpers:
helperBLEMeshAppGenericPDU: Generate Bluetooth mesh generic PDU
helperBLEMeshAccessPDU: Generate Bluetooth mesh access PDU
helperBLEMeshTransportDataMessage: Generate Bluetooth mesh transport data message
helperBLEMeshNetworkLayer: Create an object for Bluetooth mesh network layer functionality
helperBLEMeshNetworkLayerDES: Model Bluetooth mesh network layer
helperBLEMeshNetworkPDU: Generate Bluetooth mesh network PDU
helperBLEMeshNetworkPDUDecode: Decode Bluetooth mesh network PDU
helperBLEMeshLLGAPBearer: Create an object for BLE LL advertising bearer functionality
helperBLEMeshLinkLayerDES: Model Bluetooth mesh link layer
helperBLEMeshGAPDataBlock: Generate advertising data with Bluetooth mesh network PDU
helperBLEMeshGAPDataBlockDecode: Decode advertising data with Bluetooth mesh network PDU
helperBLEPHYTransmitter: Create an object for BLE PHY transmitter
helperBLEPHYTxDES: Generate and transmit the BLE waveform
helperBLEChannel: Create an object for BLE channel model
helperBLEChannelDES: Apply channel model on the received BLE waveform
helperBLEPHYReceiver: Create an object for BLE PHY receiver
helperBLEPHYRxDES: Receive and decode the BLE waveform
helperBLEPracticalReceiver: Demodulate and decode the received signal
helperBLEMeshQueue: Create an object for Bluetooth mesh queue functionality
helperBLEMeshRetransmissions: Create an object for retransmissions in Bluetooth mesh
helperBLEMeshVicinityNodes: Obtain the vicinity nodes of a given node
helperBLEMeshGraphCursorCallback: Display the node statistics on mouse hover action
helperBLEMeshVisualizeNetwork: Create an object for Bluetooth mesh network visualization
helperBLEMeshAssignNodeIDs: Assigns node IDs to all the nodes in the model
helperBLEMeshGetNodeNamesList: Get the list of nodes in the model
helperBLEMeshCreateNetworkModel: Create a Bluetooth mesh network with given configuration
helperBLEMeshUpdateStatistics: Create and update statistics in a Bluetooth mesh network simulation