What is meant by WSN simulations? In general, wireless sensor network (WSN) simulations are mainly usedfor data processing and collective sensing is the main responsible for WSN. These sensors are in the distributed architecture here simulation of framework and real-time hardware prototype is possible using WSN Simulation in Matlab.
Simulation of the sensor is mandatory to share the data or information from one node to another node through the visualization.
“This article has a piece of knowledge about Wireless Sensor Network WSN Simulation in MATLAB platform and its basic like simulation in Matlab, methodology, architecture and some demo projects. ”
Matlab is a platform that is used to construct the framework for corresponding simulations for WSN environments. Matlab is abbreviated for MATrix LABoratory. Simulink is a multi-domain environment for doing simulations and also gives a model-based design for an embedded and dynamic system.
This is a kind of software package for doing the process such as analysis and numeric computation and this software is maintained by MathWorks. This software gives a better performance that is reliable and flexible.
- Simulink is also a software package that is used to analyze, model, and simulate the dynamic system.
This Matlab/Simulink provides the customized design for the user with seamless MATLAB/Simulink. This is the introduction to Matlab/Simulink software. Here some widely used mathematical notations are used for the solution of the problem and it also stimulates the programming, computations, and visualization in an environment that is easy to use. For technical computing MATLAB is suitable this is a high-performance language for building the simulation model. Then we will discuss some methodologies that are used in WSN simulation in Matlab.
Methodologies in WSN Simulation
This kind of simulation methodologies are mainly used for the construction of various wireless sensor Network types and MATLAB is a novel field for open the doors problems.
- Simulation methodologies give support to a customized set of block libraries and interactive graphical environment these facilitate the testing, implementation, designing, and simulation in a different time with multiple numbers of systems.
These are the use of simulation methodology in WSN. Then we will move on to the next topic that is simulating a simple wireless sensor network in matlab. In this section, we mainly concentrate on two nodes that are master nodes and slave nodes
Simulate WSN using Matlab/Simulink
From the concept of simulation methodology, the WSN topology is created first. Then this network contains two kinds of sensors are Master sensor nodes and Slave sensor nodes. The functionality of this sensor is a slave node that sends the calculated data sample to the master node.
- Slave node: Consider one network which contains more slave nodes. Then connecting the first slave to the network is possible as the master node can classify the particular connection into 2500 subintervals. The length of the network is calculated by using the sum of maximum values.
- Master node: This master node is also called an initiator and the input of the master node is the signal which is produced by the channels. It has two types of output. That is
- The first one has transmitted signals it is given to channel.
- The second output is diagnostics but it contains scope and analysis.
Then we will move on to the architecture of the system this part contains transmitter and receiver, block in the transmitter, blocks in the receiver. Let us separately see each and individual part.
The architecture of WSN in MATLAB
Transmitter and Receiver
In this block, the maximum capacity of the radio signal is 1 Mbps. Here the signals can be modulated by using GFSK that is Gaussian Frequency Shift Keying.
- This architecture has Bluetooth technology that acts as a backbone of operations in transmitting time.
- Bluetooth is also known as short-range radio link technology. IT has 2.4GHz of,
- Medical band
- Industrial band
- Scientific band
Blocks in transmitter phase
Encode and Modulate
- Here at 1 Mbps of time, there is 366 bits are transmitted and these signals must be modulated using Gaussian Frequency Shift Keying that is GFSK.
- Then, if the input of frequency hopping value is 0 and sinusoid waves are generated which has the complex value that is -39MHz, and the input value is 1 then generating the sinusoid wave also complex with having -38MHz.
Sensor Signal Stage
- This block consists of a sensor that can be sense physical signals like pressure, temperature, motion, etc.
- Then the work of the transducer converts the physical signal to the electrical signal.
- This block also has an additional component ADC that is Analog to Digital converter. This conversion is possible by using 256 quantization levels.
Hop Sequence Generator
- If communication between two devices is possible by transmitting and receiving devices must have the same frequency in a particular transmission time.
- The generation of hop frequency with the range 0 to 78 is possible by using a frequency hop generator.
- It can be either a random or fixed sequence.
Up-sample to 64ksamples/s
- In this block, the input messages are converted to the higher range signal by adding zero between the samples.
Payload FEC encode
- Puncturing devices are used to encode the data with the correction method called FEC encoder.
Blocks in receiver phase
- To find the behavior of the system it compares the original signal with received signals.
Hop Sequence Generator
· Its functions are also the same in the transmitter phase
Down-sample to 8ksamples/s
- Here the input is at a lower rate because of deleting the repeated samples.
Demodulate and encoder
- The main purpose of this block is to encode the original signal and modulate the sinusoid wave into carrier wave then recover information is possible in this block.
- This block performs an un-buffer operation by converting Mi–by-M input signal into 1-by-N output.
- Here row-wise un-buffer operation works then the matrix gets the output of independent time samples.
- In this block, the rate of receiving input is must be lesser than the rate of the output signal of the block.
- In this block, having the sample period and will take only one input at a time and produce one output.
- These outputs are in any format like scalar or vector. Considering vector input then the elements have the same sample period.
So, this is the architecture of this system WSN Simulation in MATLAB. Then we will move on to some basic projects in Matlab wireless sensor network. Here we discuss the project Bluetooth low energy wireless sensor network library in MATLAB/Simulink and also advancement of WSN, advantages of Matlab. Let we will separately see every topic.
Demo Project for WSN simulation in MATLAB
Bluetooth Low Energy Wireless Sensor Network Library in MATLAB Simulink
- The main concept of this project is to simulate the interaction among Bluetooth Low Energy devices with the noise of the channel and interference.
- MATLAB Simulink elements have the model of this project.
- Different kinds of parameters are used in this project,
- Position of devices in 2-Dimension
- Distance between the devices
- Attenuation calculation
- Transmitting signals co-efficient
These are some parameters that are used in the demo project- Bluetooth Low Energy Wireless Sensor Network Library in MATLAB Simulink. Then we will move on to the advancement of WSN and some key advantages of Matlab.
Advancements of WSN
To monitor the structural integrity accurately, analysis of data and data collection is some advancement of WSN.
- Due to multiple factors, there is a chance to attack the data collection process.
- In recent times a lot of novel algorithms and protocols are created by researchers to improve performance.
Advantages of Matlab in WSN
- In MATLAB/Simulink toolkits, blocks for WSN are available with some examples.
- It also has an automatic code generation process; it’s useful to simulate the simulation model with a real-time process.
- Because the Zigbee network has customized node communication.
- Integration of hardware model is easy and it has an attractive framework for WSN.
Until we are sharing the information’s about the wireless simulation network WSN Simulation in MATLAB. In this platform, we can build more simulations and additionally have some mathematical equations. In this article, we can able to understand some new technical topics like encoding and decode, sampling, payload, etc. Our experts have a wonderful knowledge about these kinds of technical terms. So, quickly join us for your precious research projects.