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5G Communication System Using Matlab

Learn to estimate capacity, BER, and outage probability in NOMA systems using practical MATLAB code. Step-by-step guidance for communication system analysis.

4.4(176)
12,840students
4h 28m
Certificate
Dr. Khaled Ramadan
Dr. Khaled RamadanAssistant Professor

Course Content

5G Communication System Using Matlab is an all-levels Udemy course taught by Dr. Khaled Ramadan. It runs 4h 28m, is taught in English, and includes a certificate of completion. Learners rate it 4.4 out of 5 from 176 reviews, with 12,840 students enrolled. It is a paid course, first published August 2021.

This course is specifically tailored for electronics and communication engineering students, both undergraduate and postgraduate, offering a comprehensive exploration of modern wireless communication techniques. It features eight detailed outlines, each combining theoretical explanations with practical MATLAB code for simulating and visualizing key concepts. This course provides a significant time-saving advantage, streamlining months of independent research and development.

Using MATLAB, you will gain hands-on experience in:

  • Channel Capacity Calculation: Master the Shannon formula to accurately estimate channel capacity in various communication scenarios.
  • Non-Orthogonal Multiple Access (NOMA) & Orthogonal Multiple Access (OMA) Rate Analysis: Learn to calculate the achievable data rates offered by both NOMA and OMA techniques for uplink and downlink communication.
  • Impact of Successive Interference Cancellation (SIC): Investigate how imperfect SIC affects the rate capacity of downlink NOMA systems.
  • Fixed Power Allocation (FPA) in NOMA: Analyze the influence of NOMA Fixed Power Allocation (FPA) on Bit-Error-Rate (BER) performance.
  • NOMA vs. OMA User Capacity: Understand the relationship between the number of users supported by NOMA compared to traditional OMA techniques.
  • NOMA User Paring: Delve into the concept of user paring in NOMA and learn practical methods for performing efficient user pairing.
  • Power Allocation Strategies in NOMA: Explore and implement both fixed and dynamic power allocation schemes in NOMA, validating their performance through simulations.
  • BER Performance on Rayleigh Fading Channels: Estimate the Bit-Error-Rate (BER) performance of NOMA communication systems operating over a Rayleigh fading channel.
  • NOMA Channel Capacity Estimation: Learn to calculate the achievable channel capacity of a NOMA communication system when the channel is subject to Rayleigh fading.
  • Outage Probability Analysis in NOMA: Estimate the outage probability of a NOMA communication system operating over a Rayleigh fading channel, crucial for reliable communication design.
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