This presentation is about the array antenna, its types,advantages and LMS algorithm.

1. Array Antenna and LMS
Algorithm
Shivi Jain
10BEC0338
Slot - C1 1

2. Array Antenna
• Multiple antenna elements
• Isotropic radiators
• Current of different amplitude and phase
• Array pattern can be changed
• Total pattern is the sum of individual radiation
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3. Array Antenna
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4. Types of Array Antenna
• Active and passive array antenna
• Linear array antenna
• Planar array antenna
• Cylindrical array antenna
• Conical array antenna
• Digital array antenna
• Multibeam array antenna
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5. Types of Array Antenna
• Multifaced array antenna
• Multifrequency array antenna
• Adaptive array antenna
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6. Active and Passive Array
• Active – active element like oscillator
connected to the path of radiator
• Classified as receiving, transmitting and
tranceiving antenna
• Radiated power increased
• Thermal loss decreased
• Reliability increased
• Use transmit/receive (T/R) module
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7. Active and Passive Array
• Passive – has central transmitter and receiver
• Phase shifter located at each radiating
element
• All elements excited by common oscillator or
connected to common receiver
• Feed network is the main part connecting
elements
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8. Active and Passive Array
• Classified as receiving, transmitting and
transceiving antenna
• Used in variable purpose radars
• Cheapest phased array
• Less number and cost of components
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9. Active and Passive Array
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10. Linear Array
• Consists of group of identical elements
• Elements placed in 1-D
• Elements placed in specified direction in a
straight line
• Spacing between element may be equal or not
• Used in analysis of directional properties of
arrays
• Building blocks for forming array of elements
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11. Linear Array
• Design of antenna is practical and simpler
• Easy fabrication
• Individual elements may be wire dipoles,
loops apertures or any other type
• Total field = vector superposition of field
radiated by individual elements
• AFn(normalized) = 1/n[sin(nψ/2) / sin(ψ/2)+
where Afn is the normalized array factor.
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12. Linear Array
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13. Planar Array
• All elements in a single plane
• Elements occupy a definite area
• Configurations – rectangular, triangular,
square, hexagonal.
• Provides large aperture
• Used in directional beam control by varying
relative phase of each element
• Each radiating element has its own phase
shifter
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14. Planar Array
• The elements are in the form of matrix
• It is two dimensional
• Beam steering in two planes is possible
• Digital beamforming can be done
• Arrangement of elements is complicated
• More electronically controlled phase shifters
are required
• Cost is more
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15. Planar Array
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16. Cylindrical Array
• Radiators positioned on a cylindrical surface
• Radiators used – wire and slot dipoles, open
ended waveguides and horns, spiral and
dielectric rod antennas
• Selection of radiator depends on wavelength
and required bandwidth
• Narrow bandwidth – 10000 elements
• Used where azimuthal scanning with constant
beam shape and gain is required
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17. Cylindrical Array
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18. Conical Array
• Radiators positioned on a conical surface
• Wavelength less than 0.5λ should be used for
the array element spacing
• To use radiators efficiently – beam axis
pointed to the required direction to have
maximum gain
• Narrow bandwidth – around 10000 elements
• Maintains high gain and EIRP in forward
hemisphere
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19. Conical Array
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20. Digital Array
• Is a phased array
• Signal is converted into digital code
• Further processing, formation of antenna
pattern and signal processing performed in a
digital computer
• The computer performs digital beamforming
• Instantaneous shaping of array pattern in any
direction
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21. Digital Array
• Can generate adaptive array patterns of
arbitrary shape
• Error is minimized
• Complex hardware and software
• Fast and efficient algorithms required to
reduce complexity
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22. Digital Array
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23. Multibeam Array
• Supports generation of several beams
• Multibeam feed is used for above
• Beams are used for surveillance of a sector
• Each beam has a separate input channel
• Uses multiple beam forming network
• This network has quadrature directional
couplers and fixed phase shifters
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24. Multibeam Array
• Provide high quality of service
• SDMA is used to design the antenna
• SDMA provides high user capacity in a limited
frequency spectrum
• Used in radar applications, satellite
communication and mobile communication
• Interference is minimized
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25. Multibeam Array
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26. Multi-faced Array
• System of planar arrays
• Arrays arranged in a form of a regular
polyhedron
• Performance increases as the coverage range
becomes wider
• No clear improvement gained by using more
than 10 faces
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27. Multi-faced Array
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28. Multifrequency Array
• Operates over several frequency bands
• Can be formed by many techniques
• By using convex multifrequency arrays with
distributed multifrequency radiators
positioned on convex, curvilinear surfaces
• By using multifrequency or wideband
radiators and frequency separation filters
• By the merging of one array into another
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29. Adaptive Array
• Consists of N element array
• Appropriate choice of weighting coefficients
• Weights placed between antenna elements
and a combining network
• Weight should be capable of changing the
amplitude and phase of received signal from
each element
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30. Adaptive Array
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31. Adaptive Array
• Interference can be reduced by:
• Maximization of SINR at output of array
• Minimum mean square deviation of received
signal from a reference level at output of array
• Minimum interference power at array output
• Maximum probability of detection of the
desired target signal
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32. Advantages of Array Antennas
• Increase in the overall gain
• Provides diversity reception
• Cancels out interference from a particular set
of directions
• Steer the array such that it is more sensitive in
a particular direction
• Used to determine the direction of arrival of
incoming signal
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33. Advantages of Array Antennas
• To maximize the signal to interference noise
ratio (SINR)
• Provide high array gain by using simple
antenna elements
• Provide a diversity gain in multipath signal
reception
• Enabling of array signal processing
• Provide capability of steerable beam as in
smart antennas
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34. Adaptive Array and LMS Algorithm
• Adaptive antenna – multibeam adaptive array
• Gain pattern adjusted dynamically
• Used to mitigate interference and improve
spectral efficiency in mobile systems
• Digital beamforming antennas (DBF) are
developing as advanced phase array antennas
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35. Adaptive Array and LMS Algorithm
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Adaptive array configuration

36. Adaptive Array and LMS Algorithm
• LMS (Least Mean Square) error algorithm is
used to cancel interference
• It was developed by Widrow et al
• Further work was done by Frost and Griffiths
• They worked to ensure that the desired signals
were not filtered out along with the unwanted
signals
• LMS algorithm uses continuous adaptation
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37. Adaptive Array and LMS Algorithm
• Interference rejection achieved by optimally
determining the array weights
• The LMS algorithm takes advantage of the
following two points:
• The MSE when plotted against the filter
coefficients is a quadratic, bowl-shaped one
with a unique minimum
• The gradient of a function always points
towards the maximum of the function
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38. Adaptive Array and LMS Algorithm
38Example MSE surface for N = 2

39. Adaptive Array and LMS Algorithm
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The Adaptive Processor

40. Adaptive Array and LMS Algorithm
• In the Steepest Descent Optimization method,
the weight vector is made to “evolve” in the
direction of the negative gradient
• Disadvantage - complex computation involved
in finding the values of the r and R matrices
• R - auto correlation matrix of received signal
• r – cross correlation vector between the
desired signal and the received signal
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41. Adaptive Array and LMS Algorithm
• LMS algorithm - simplification of the Method
of Steepest Descent
• Instantaneous values of R and r are used
instead of their actual values
• Simple expression for weight adaptation
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42. LMS Algorithm Steps
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43. LMS Algorithm Steps
• We assume that the signals involved are real-
valued
• The LMS algorithm changes (adapts) the filter
tap weights so that e(n) is minimized in the
mean-square sense
• LMS algorithm is simplified form of steepest
descent algorithm and replaces the cost
function by its instantaneous coarse estimate
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44. LMS Algorithm Steps
• E{e2[n]} changes to e2[n]
• e2[n]is the mean square error between the beam-
former output y(n) and the reference signal
• Substituting the above value in the steepest
descent recursion, we obtain w[n + 1] = w[n] -
μ*▼{e2[n]}]
• µ is the step-size parameter and controls the
convergence characteristics of the LMS algorithm
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45. LMS Algorithm Steps
• Now ▼{e2[n]} = -2e(n)x(n)
• Finally we get the LMS recursive function as:
w*n + 1+ = w*n+ + 2μx*n+e*n+
• Therefore the summary can be given as:
• Weight vector : w[n]
• Input vector : x[n]
• Desired output : d[n]
• Filter output : y[n]
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46. LMS Algorithm Steps
• Weight vector updated : w[n+1]
• Output : y[n] = wt[n]x[n]
• Error : e *n+ = d*n+ − y*n+
• Weight : w*n + 1+ = w*n+ + 2μx*n+e*n+
• LMS is simple in implementation
• Stable and robust performance against
different signal conditions
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47. References
• ‘LMS and SMI algorithms for spatial adaptive
interference rejection’ by Vijaya Chandran
Ramasami; March 16, 2001.
• ‘GPS interference mitigation for small UAV
applications’ by Joy Li; School of Electrical and
Electronic Engineering; The University of
Adelaide; Adelaide, South Australia; March
2009.
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48. References
• ‘Theory and Analysis of Adaptive Cylindrical
Array Antenna for Ultrawideband Wireless
Communications’ by Malek G. Hussain, Senior
Member, IEEE; IEEE Transactions on Wireless
Communications, Volume 4; November 6,
2005.
• ‘Passive Phased Arrays for Radar Antennas’ by
EMS Technologies, Inc.; Space and Technology
– Atlanta; December 2005.
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49. References
• ‘Adaptive Array Antenna for Mobile
Communication’ by Isamu Chiba, Rumiko
Yonezawa and Kazunari Kihira; Mitsubishi
Electronics Corporation, Japan; IEEE 2000.
• ‘An Overview of Adaptive Antenna Systems’
bu Hafeth Hourani; Helsinki University of
Technology Communications Lab;
Postgraduate course in Radio Communications
(2004/2005).
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50. References
• ‘Interference Rejection of Adaptive Array
Antennas by using LMS and SMI algorithms’
by Kerim Guney, Bilal Babayigit and Ali
Akdagli; Turkey.
• http://www.antennatheory.com/arrays/main.
php
• http://www.radartheory.8m.com/antenna15.h
tml
• http://cwww.ee.nctu.edu.tw/course/asp/ASP0
4.pdf
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51. References
• http://en.wikipedia.org/wiki/Antenna_array
• http://personal.ee.surrey.ac.uk/Personal/D.Jef
feries/antarray.html
• http://en.wikipedia.org/wiki/Phased_array#Ac
tive_Phase_Array
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