PTCEC335 Antenna Design Syllabus:

PTCEC335 Antenna Design Syllabus – Anna University Part time Regulation 2023

COURSE OBJECTIVES:

● To introduce the basic concepts of antenna arrays for smart antenna design
● To discuss the random variables and processes for angle of arrival (AOA) estimation
● To describe different algorithms used for AOA estimation
● To introduce the concepts of fixed weight beamforming
● To introduce the concept of adaptive beamforming

UNIT I ANTENNA ARRAY FUNDAMENTALS

Linear arrays: Two element and Uniform N element array – Array weighting: Beam steered and weighted arrays – Circular arrays – Rectangular planar arrays – Fixed beam arrays – Butler Matrices – Fixed sidelobe cancelling – Retrodirective arrays: Passive and active retrodirective arrays.

UNIT II PRINCIPLES OF RANDOM VARIABLES AND PROCESSES

Definition of Random Variables – Probability Density Functions – Expectation and Moment – Common Probability Density Functions – Stationarity and Ergodicity – Autocorrelation and Power Spectral Density – Correlation Matrix

UNIT III ANGLE OF ARRIVAL ESTIMATION

Fundamentals of Matrix Algebra: Vector basics – Matrix basics – Array Correlation Matrix – AOA Estimation Methods: Bartlett AOA estimate, Capon AOA estimate, Linear prediction AOA estimate, Maximum entropy AOA estimate, Pisarenko harmonic decomposition AOA estimate, Min-norm AOA estimate, MUSIC AOA estimate, Root-MUSIC AOA estimate, ESPRIT AOA estimate

UNIT IV SMART ANTENNAS: FIXED WEIGHT BEAMFORMING

Introduction – Historical Development of Smart Antennas – Fixed Weight Beamforming Basics: Maximum signal-to-interference ratio, Minimum mean-square error, Maximum likelihood, Minimum variance

UNIT V SMART ANTENNAS: ADAPTIVE BEAMFORMING

Adaptive Beamforming: Least mean squares, Sample matrix inversion, Recursive least squares, Constant modulus, Least squares constant modulus, Conjugate gradient method, Spreading sequence array weights, Description of the new SDMA receiver.

30 PERIODS
PRACTICAL EXERCISES: 30 PERIODS

1. Write a MATLAB code to estimate the radiation pattern of a linear array and N element uniform array
2. Write a MATLAB code to estimate the AOA using MUSIC and ESPRIT algorithm
3. Write a MATLAB code to estimate the weights of the array. Using the final weights estimate the array factor and the mean square error.
4. Write a MATLAB code to dynamically alter the main lobe direction based on the information of AOA.

COURSE OUTCOMES:

At the end of this course, the students will be able to:
CO1: Describe the basics of phased array antennas
CO2: Understand random process and its application in Smart antennas
CO3: Estimate the weights of the antenna array based on the angle of arrival
CO4: Analyze the fixed weight beamforming in smart antennas
CO5: Analyze adaptive beamforming in smart antennas

TOTAL 60 PERIODS
TEXT BOOKS

1. Frank Gross, Smart antennas for wireless communications, McGra-Hill, 2006.
2. S. Chandran, Adaptive antenna arrays, trends and applications, Springer, 2009.

REFERENCES

1. T. S. Rappaport, Smart antennas: Adaptive arrays, algorithms and wireless position location, IEEE Press, 1998.
2. Robert A.Monzingo, Randy L. Haupt and Thomas W.Miller, Introduction to Adaptive arrays, 2nd Edition, IET, 2011.
3. Thomas Kaiser, Smart Antennas: State of the Art, Hindawi, 2005