Module 1: Fundamentals of signal processing: Continuous and Discrete signal : Signals and Hilbert space, Sampling, DTF, Filtering, Finite impulse response filter, FFT,
Module 2: Probability, Random Variables, and Stochastic Signal Processing: Probability axioms, Statistical Averages and Joint Moments , Moment Generation Function
Module 3: Functions of Random Variables , Q-Function Multivariate Gaussian Distribution ,Uniform Density Function , Chi-Square Distribution, F Distribution ,Rayleigh Distribution, Rice Distribution, Central Limit Theorem ,
Module 4: Discrete-Time Random Process, Stationary Processes, Estimated Functions , Power Spectrum , Stochastic Processes for Linear Systems. Detection of signal in noise: Bayes criterion, MAP, ML,NP, Min-Max, Multiple hypothesis,
Module 5: Composite hypothesis and ROC curves and performance. Channel Estimation and blind identification: Channel estimators–ML, LS, GLS, MMSE, Adaptive Channel estimators: LMS, RLS, Channel models and blind identification-SISO, SIMO,MIMO.
Module 6: Adaptive Equalizers: Linear, Adaptive Linear, Fractionally spaced, Decision feedback, Space–time and diversity.
Module 7: Design of a Digital Communication System: The Communication Channel ,The AM Radio Channel, The Telephone Channel Modem Design-The Transmitter , Digital Modulation and the Bandwidth Constraint , Signaling Alphabets and the Power Constraint,
Module 8: Modem Design: the Receiver, Hilbert Demodulation, The Effects of the Channel, Adaptive Synchronization, Carrier Recovery, Timing Recovery.
Module 9: DSP Hardware and implementation technologies for communication: TMS processors and SDR. Hardware limitations, A/D, filters, antennas, AGC, etc. Processing, programmability (flexibility) vs power consumption
Module 10: Digital signal processing role in SDR, and some examples FPGA/DSP and mixed programming platforms.

Study of fundamentals of signal processing, time and frequency domain analysis of the signals.

Study of probability theory and random processes.

Design of a digital communication system.

DSP hardware and implementation technologies for communication.

CO1: Learning the basics of Signal Processing
CO2: Understanding the basics of probability theory and random variables.
CO3: Design of equalizers, modems DSP hardware and their applications.
CO4: Learning the design of a basic communication system
CO5: Implementing DSP hardware for communication.

John Minkoff, Signal Processing Fundamentals and Applications for Communications and Sensing Systems, Artech House , New Edition,2002

Hippenstiel, Ralph Dieter, Detection theory: applications and digital signal processing, CRC Press,2002

Sen M Kuo Bob and H Lee, Real time signal processing, John Wily & Sons, Inc. 2001

John Minkoff, Signal Processing Fundamentals and Applications for Communications and Sensing Systems, Artech House , New Edition,2002

Hüseyin Arslan (Ed.), "Cognitive Radio, Software Defined Radio, and Adaptive Wireless Systems," Ser.Signals and Communication Technology, xviii, 470 p., I. edition, ISBN: 978-1-4020-5541-6, Springer, August 2007