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
