Signal Processing in Wireless Communications
( 24 Modules )

Module #1
Introduction to Signal Processing in Wireless Communications
Overview of signal processing in wireless communications, importance, and applications

Module #2
Fundamentals of Signal Processing
Review of signal processing basics:signals, systems, Fourier transform, and filtering

Module #3
Wireless Communication Fundamentals
Introduction to wireless communication systems, modulation, and demodulation

Module #4
Channel Models for Wireless Communications
Characterization of wireless channels:path loss, fading, and shadowing

Module #5
Signal Processing Techniques for Channel Estimation
Methods for estimating wireless channel parameters:LS, ML, and Bayesian estimation

Module #6
Channel Equalization Techniques
Types of channel equalizers:linear, nonlinear, and adaptive equalizers

Module #7
Introduction to Spread Spectrum Systems
Fundamentals of spread spectrum systems:advantages, types, and applications

Module #8
Direct Sequence Spread Spectrum (DSSS)
Principles of DSSS:PN sequences, spreading, and despreading

Module #9
Frequency Hopping Spread Spectrum (FHSS)
Principles of FHSS:frequency hopping, and hopset design

Module #10
Signal Processing for Multi-User Detection
Techniques for multi-user detection:decorrelating detector, MMSE detector, and successive interference cancellation

Module #11
Space-Time Processing
Introduction to space-time processing:antenna arrays, beamforming, and spatial filtering

Module #12
MIMO Systems
Fundamentals of MIMO systems:channel capacity, spatial multiplexing, and diversity gains

Module #13
Signal Processing for OFDM Systems
Principles of OFDM:modulation, demodulation, and channel estimation

Module #14
Pilot-Assisted Channel Estimation in OFDM
Pilot-aided channel estimation techniques in OFDM:least squares, MMSE, and compressive sensing

Module #15
Compressive Sensing in Wireless Communications
Introduction to compressive sensing:principles, applications, and algorithms

Module #16
Cooperative Signal Processing
Cooperative communication techniques:amplify-and-forward, decode-and-forward, and compress-and-forward

Module #17
Cognitive Radio and Dynamic Spectrum Access
Cognitive radio principles:spectrum sensing, dynamic spectrum access, and interference management

Module #18
Signal Processing for IoT and 5G Applications
Signal processing techniques for IoT and 5G:low-latency, low-power, and massive connectivity

Module #19
Machine Learning for Signal Processing in Wireless Communications
Introduction to machine learning for signal processing:supervised, unsupervised, and reinforcement learning

Module #20
Deep Learning for Wireless Communications
Applications of deep learning in wireless communications:channel estimation, signal detection, and resource allocation

Module #21
Software-Defined Radio and Real-Time Signal Processing
Software-defined radio architectures and real-time signal processing:platforms, tools, and implementation

Module #22
Signal Processing for 5G New Radio (5G NR)
Signal processing techniques in 5G NR:beamforming, channel estimation, and massive MIMO

Module #23
Signal Processing for Millimeter Wave (mmWave) Communications
Signal processing challenges and techniques in mmWave communications:beamforming, channel estimation, and propagation modeling

Module #24
Course Wrap-Up & Conclusion
Planning next steps in Signal Processing in Wireless Communications career

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Signal Processing in Wireless Communications ( 24 Modules )

Signal Processing in Wireless Communications
( 24 Modules )