The Complete Matlab Course for Wireless Comm. Engineering

🎉 The Complete Matlab Course for Wireless Communication Engineering 📡

Course Headline: Dive into Mastering Matlab for BER, CFO & PAPR Estimations in OFDM and NOMA Systems!

About the Course:

This comprehensive online course is tailored for undergraduate and postgraduate students, as well as professionals working within the electronics and communication engineering fields. With over 31 introductory lessons, this course provides a deep-dive into understanding and applying Matlab for performance analysis of modern communication systems. By following the theoretical framework followed by practical simulations, you'll save countless hours of research and development time, all while mastering the intricacies of Matlab within the context of wireless communications.

Course Highlights:

• Understanding OFDM Systems: Learn how to simulate an Orthogonal Frequency Division Multiplexing (OFDM) communication system using Matlab and analyze its performance over Additive White Gaussian Noise (AWGN) channels and Rayleigh fading channels.

• Bit Error Rate (BER) Analysis: Gain insights into estimating BER for OFDM systems under various conditions, including the impact of different mapping schemes and equalization techniques.

• Carrier Frequency Offset (CFO) & Mean Square Error (MSE) Estimation: Explore how to model and measure the effects of CFO and optimize system performance using MSE criteria.

• Peak-to-Average Power Ratio (PAPR) Measurement: Discover techniques to estimate PAPR for OFDM systems, which is crucial for power amplifier design and energy efficiency.

• Non-Orthogonal Multiple Access (NOMA): Examine BER performance for pre-coded downlink NOMA systems using FFT/DST/DCT-OFDM and understand the impact of localized and interleaved sub-carrier mapping on system performance.

What You'll Learn:

1. BER over SISO-OFDM with AWGN: Analyze the BER performance in an OFDM system without and with equalization over an AWGN channel using FFT.

2. Rayleigh Fading Channel Model: Learn to simulate a Rayleigh fading channel based on the Jakes fading model, crucial for understanding wireless channel variations.

3. BER over SISO-OFDM with Rayleigh Fading & Equalization: Study the impact of equalization on BER estimation in an OFDM system over a Rayleigh fading channel.

4. CFO Estimation for OFDM: Investigate the effects of CFO and learn how to estimate its performance using FFT and CP symmetry property over both AWGN and Rayleigh fading channels.

5. MSE Analysis for CFO in OFDM: Understand the process of estimating CFO-induced performance degradation in OFDM systems using MSE criteria.

6. BER Performance with DST and CP/EQ: Learn how to estimate BER for DST-based OFDM systems with different equalizers over a Rayleigh fading channel.

7. BER with DCT and Equalization for OFDM: Explore the implications of using DCT instead of FFT or DST in an OFDM system, including the effects of different equalizers on BER performance.

8. PAPR Estimation Techniques: Understand how to measure PAPR for both FFT and DST/DCT-based OFDM systems and its significance in power management.

9. Proposal for BER Code in a Multi-Antenna Configuration: Get hands-on with proposing a general Matlab code for BER estimation in an Nt×Nr configuration, applicable to various multi-antenna scenarios like MIMO.

10. BER Estimation for Pre-coded NOMA Systems: Dive into the world of NOMA and study how to estimate BER performance for FFT/DST/DCT pre-coded downlink NOMA systems over Rayleigh fading channels.

11. PAPR Analysis for NOMA Systems: Analyze the PAPR in DST/DCT-based NOMA systems, which is essential for designing energy-efficient communication systems.

Join us on this educational journey to master Matlab and its applications in modern wireless communication systems! 💻✨

Enroll now and transform your skills with hands-on Matlab simulations and theoretical insights into BER, CFO, and PAPR estimations for OFDM and NOMA systems. Let's make complex concepts understandable and practical through this unique learning experience.