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Mobile & Satellite Communication Technologies

Part 1. Mobile Fading Channels: The objective of this task is to investigate the main types of mobile

fading channels with the use of MATLAB Simulink environment and channel visualization tools. You

are required to model and simulate the following types of fading: Flat Fading, Frequency Selective

Fading, Slow Fading, and Fast Fading.

Modelling using Simulink: Construct a simple model in Simulink environment to consist of a data

source, binary PSK (BPSK) modulator and fading channel blocks. You may use a random data source

from the “Communications Blockset/Sources”, BPSK modulator from “Communications

Blockset/Modulation” and the “Multipath Rayleigh Fading Channel” from the “Communications

Blockset/Channels” libraries. You need to enable the “Open Channel Visualization” option available

within the multipath Rayleigh fading channel block to obtain plots in different domains (e.g. impulse

response, frequency response, multipath components and gains, Doppler spectrum etc.).

Simulation Results and Analysis: Set all the various parameters and run your simulations. Obtain

results and perform analysis supported by calculations and comparisons with theoretical to verify the

characteristics of each channel under investigation. You can change the settings to investigate channel

characteristics for different scenarios. Remember to include the Simulink block diagram, settings,

results, and analysis in your report.

Part 2. Fading Mitigation Methods: The aim of this task is to conduct performance investigation of

space diversity and spread spectrum as two techniques to mitigate fading. You are required to simulate

the following systems: (1) BPSK communication system (as a base for comparison purposes). (2) BPSK

with space diversity. (3) BPSK with spread spectrum.

System Modelling with Simulink: For System 1 you can use the model in Part 1 by adding the BPSK

demodulator block (from the “Communications Blockset/Modulation” Library). For System 2 you can

use the same model as system 1 but modify to include two channels and receive combining system for a

dual antenna receive diversity system. For System 3 you may use the spread spectrum Simulink Demo

model already available within MTALAB library. For each system you need also to add the Additive

White Gaussian Noise (AWGN) Channel Block from the “Communications Blockset/Channels” Library

after the fading block. To obtain the Bit Error Rate (BER) results you need to add the “Bit Error Rate

Calculation” block from “Sinks” within your models.

2

Simulation Results and Analysis: Obtain the BER versus Eb / No (Energy per bit-to-noise spectral

density) results for each system. You can use the “BER tools” to plot the results and for ease of

comparisons. Perform comparisons and analysis study including theoretical. Pay attention to the type of

fading channel you are using for each system. Spectrum results are also important to be obtained using

the frequency scopes available within Simulink.

Skills: Wireless

See more: ber performance bpsk using simulink, analysis bpsk model space diversity plot, use of binary, simple binary, open systems technologies, objective c tools, objective c mobile, library scenarios, data set visualization, characteristics of, c.a. technologies, bit frequency, bit binary, binary frequency, binary bit, aim communications, simulink visualization multipath rayleigh fading channel, space diversity block simulink, white space analysis, types of tools, part channel, different types of tools, communication is, simulink matlab, simulation models

About the Employer:
( 0 reviews ) Falun, United Arab Emirates

Project ID: #1268623

3 freelancers are bidding on average £219 for this job

hmramezani

I am Hamid Ramezani, a PhD student at TU Delft. Currently, I am working in the field of signal processing for communications. To get more information about me please go to the following link: [url removed, login to view] More

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wahab14

hi, i can do it

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Elecguru011

Hi , I am create a matlab app for it using GUIDE in matlab.

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