why aa(sa)

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ADAPTIVE ANTENNAS. PROF. A.M.ALLAM

1

WHY ADAPTIVE (SMART)ANTENNAS?

ADAPTIVE

ANTENNAS

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1-Why are smart antenna (SA) and adaptive antennas (AA) emerging now?

The concept of smar t antennas has been around since the late 50s[13]

AAsystems capabil i ties where limi tedbecause adaptive algor i thmswere usuall y implemented inanalog hardware

ADCs, which have high resolu tions and sampling r ates up to 100 GSa/s [4] makes the dir ect

digi tization of most radio f requency (RF) signals possible in many wir eless applications

I n addition, DSP can be implementedwith high speed paral lel processingusingf ield

programmable gate arrays (FPGA)

The global demand for al l f orms of wi reless communication and sensing continues to grow at a

rapid rate, SA( or AA ;where an adaptive algor i thms are involved)are the practical realization

of the array signal processingand have a wide range of interesting appli cations:

The rapid growth in telecommunications aloneis suf fi cient tojusti fy the incorporation of SA or

an AA to enable higher system capacities and data rates

Mobile wireless communications [5] -Software-defi ned radio [6, 7]-WLAN [8] - Wir eless localloops (WLL) [9]-M obil e I nternet-Wireless metropoli tan area networks (WMAN) [10]-Satell ite

based personal communications services-radar [ 11,12]- Remote sensing-Mobil e ad hoc networks

(MANET) [13]-H igh data rate communications [14]- Satell ite communications [15]-M ulti ple In

Mul tiple Out (M IMO) systems [16]-Waveform diversity systems [17]

The technologyrequi red to make the necessary rapid and computational ly intense calcul ations

has only emerged recently

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Transmission over TL are cost effective, more attenuation, more power loss

Transmission over OF are excellentbut expensive

Approach

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4

COMPRESS DATA FOR

EFF ICIENT TRANSMI SSION

ADDI NG SOME BI TS FOR

DETECTION AND

COORECTION

Reducing mul tipath propagation effects

I ncreasing channel capacity (in ter ference cancellation)

Enhancing S/N

M in imizing power consumption

Eff icient spectrum use

Immuni ty to noise or jamming

But it needs

Wireless transmission is the best cost effectiveness

Transmission over TL are cost effective, more attenuation, more power loss

Transmission over OF are excellentbut expensive

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On the other hand there are two main problems in any communication

systems:

1-How to acqui remore capacityto increase the number of user

at lower cost maintaining the QoS

2-How to obtain greater coverageto decrease the inf rastructure and

maintenance cost

i.e., the two requi rements for the service provider are

CAPACITY & COVERAGE

which are inversely related

Let us see the multiple access techniqueswhich can achieve

large number of users for the same cost

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A unique frequency

slot is assignedto eachuserfor the duration of

their call

The number of

userswithin a cell

is determined

by the number of

distinct frequency

slots available

Frequency

FDMA

At the same frequency

a user can access thechannel at any

specif ic time

Each user is assigned

a distinct time slotto

access the channel

Time

TDMA

I t is a spread spectr um

technique, which usesspreading codes to allow

the users to transmit

simul taneously at the

same frequency

Each users signal

occupies the entire

bandwidth

CDMA

Space diversity is the

main idea of adaptive or

smart antennas. I t allows

dif ferent usersto use the

same spatial system

resources

SDMA

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2-Evolution f rom omnidirectional to smart antennas (SA)

(TECHNOLOGY DEVELOPMENT LEVEL) [18]

To achieve the capacityrequir ed for

thousands of subscribers for limited

number of channels or frequencies,

a sui table cellular structur e is to be

designed Cell

Sector

Base stati on

At the center of each cell, a base station

equipped with an omnidirectional

antennawith certain bandwidthCell ular structure

Cellular networks divide a overage

area into mul tiple cell s, each has its

own radio inf rastructure and users

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Frequency reusedis applied for di ff erent cell

clusters to increase the number of subscr ibersCluster

Omnidirectional antennatr ansmits equal

intensity in azimuth plane and directive in

elevation, hence, only small percentage of the

total energy r eaches the desired direction

As the number of users increases, more interference

occurs for those in the same or adjoining cell sand hence

reducing the capacity

Cell spli ttingis the immediate solution for th is

problem. I t subdivides a crowded cellinto smallercells called micro cell s, each with its own base

stationand a corresponding reduction in antenna

height and transmitting powerare achieved

Disadvantages for cel l spli tting; i t' s costlydue to

install ing new base stations, increasing the number of

handoffs and a higher processing loadper subscriber

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Sectorization is the solution : antenna system ( phased ar ray) are replacing the

omni directional antenna. I t provides more frequencies for more subscr iber per

coverage area. This is call ed the sectoring technique

Typical ly, a cel l is sectorized into three sectors of 120each

I t improves signal-to-

interference(S/I ) ratio and

capacity

Co-Ch I is the inter ference between adjacent

clusters

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The penal ty due to channel sectoringat the base station i s an increase in the

number of antennas at base stations

Diversity offers an improvement in the

effective strengthof the received signalby

mitigating the mul tipath effects using:

-Switched diversity: at a given moment,

the system continuall y switches between

antennas (connects each of the receivingchannels to the best serving antenna)

- Combiningdiversity : This approach

corrects the phase error i n two multipath

signalsand effectively combines the

power of both signals to produce gain.

Other diversity systems, such as maximalratio combin ing systems, combine the

outputs of al l the antennas to maximize

the ratio of combined received signal

energy to noise

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Al though this approach mi tigates severe mul tipath fading, in high-interference

envi ronments, the simple strategy of l ocking onto the strongest signal or extr acting

maximum signal power from the antennas is clear ly inappropriateand can resul t in

clear reception of an interfererrather than the desired signal

The need to transmit to numerous users more eff iciently without compounding the

inter ference problem led to the next step of the evolution antenna systems

that intell igentl y in tegrate the simul taneous operation of diversi ty antenna elements

( SMART ANTENNAS OR ADAPTIVE ANTENNAS )

A base-station with

circular adaptive

antenna arr ays

Ar ray of simple10

dBi dipole antenna

elements operating

at 2 GHz of size ~

0.5* 0.75 m

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Perform

ance

System complexi ty

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Hence, SA can integrate radio intel l igence of the DSP with antenna array

technologyto:

Enhance communication system performanceincluding

Improve link quality for tr ansmission and reception

I nter ference cancell ation on the up and down l inks

SNR improvement due to antenna gain

M itigation of f ading

Capacity

Coverage range

Quali ty of service, (QoS), Bi t rate, Mobili ty rate

Di rectionall y send down li nk in formation

Save energy

Provides N-fold diversity gain

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)SOIdir ect the beam maxima to the signal of interest (Beam steer ing:-1

)SNOIdirect the beam minima to the signal not of interest (Beam nul li ng:-2

allowing different users to use the same spatial systemSpatial diversity:-3

resources (SDMA)

This can be accomplished by:

There are many terms commonly used to describe SA(array

antenna with processor to perform the beam steering ) l ike

AA (i f the adaptive algori thms involved) ,

intel l igent antennas , digi tal beam forming, phased array

with signal processor, spatial processing, SDMA,

ADAPTIVE ANTENNAS PROF A M ALLAM

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]18Analogy of auditory and electronic adaptation [-3


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Defini tion of Smart or Adaptive Antennas (SA or AA)-4

A system consisting of an antenna arrayand an adapti ve processorthat can perform

filteringin both the spaceand frequency domain

An antenna that controls its own pattern, by means of feedback control, while the

antenna operates. Some adapti ve antennas also control their own frequency response

An adaptive or a smart antenna is an antenna arr aywith a digital or adaptive signal

processorin order to control i ts pattern direction and power intensity

Any antenna arr ay, terminated in a sophisticated signal processor, which can adjust

or adapt i ts own beam pattern in order to emphasize signals of interest and to

min imize in ter fering signals


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Typical block diagram of SA

I t is a traditional antenna array

I t i s a f ixed beam array where the main lobe can be steered by

def ining the f ixed array weights w

I s it an adaptive

array?

X weightsBeam pattern

NoNo

NoNo No

I s neither smart nor adaptive


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I f the algorithmsused

are adaptiveit is

called adaptive array

The complex weight computation based ondifferent cri ter ia is incorporated

in the signal processor in the form of software algorithms

I t is an smart array

I t needs a

reference signal

or

DOA

X weights

Output y

Desired y

Same?

No,error

X modif ied

weights

Optimum y

Computemodif ied w

Modif ied Output y

Same?

yes


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Adaptive Signal Processor:The weights are continuously adjusted by

the adaptivesignal processor (AA) in order

to achieve the input function

Antenna Array:antenna elements are assumed to be identical wi th an

nondirectional pattern in the azimuthal ly plane

Complex Weights:they adjust the ampli tude and phase of the signal

which are computed by the DSP uni t

Components of SA (AA) System

I t should be pointed out that the signal processing is carr ied out in base band i.e.,:

Antenna

system

RF

F ront end

ADC; Digital

frequency

conversion

Digital

signal

processingRF IF BASE

BAND

-The signal is passed from each antenna element to the RF front end where LNPA,

mixers and analogue f i l ters are used for down conversion to IF

-The signal i s converted to digi tal base band using ADC and combined using smart

algori thm in a digital signal processor


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The smart antennas or adaptive arrays can be

abstracted to beam forming techniques

ADC

ADC

ADC

Down convert

Down conver t

Down conver t

RF SECTION SMART AND SIGNAL PROCESSING SECTI ON


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Evolution of practical SA as a part of practical system-5

-Used on uplink only (user is transmitting and the base station is receiving)

-I ncrease the gain at the base station, both the sensiti vity and range are increased,the concept is called high sensitivity receiver (HSR)

Implemented in mobile communication systems

F irst phase:

-Used on downl ink (base station is transmitting and the user is receiving) in addition to

HSR

-I ncrease the gain on both upl ink and downlink, which impli es a spatial f il teri ng in bothdir ections, the concept is call ed spatial fi ltering for inter ference reduction (SF IR)

Second phase:

Third phase:SDMA

multibeam

system

-Ful l space division mul tiple access (SDMA)

More than one user can be allocated to the same physical

communications channel simultaneously in the same cell separated by

angle. Each beam former creates a maximum toward each of i tsdesired user whi le nul l ing other users /interferers

-I t is a separate mul tiple access method, but i s usual ly combined with

other mul tiple access methods (FDMA, TDMA, CDMA)

SDMAall ows more than 8 fu ll -rate users( l ike GSM) to be served in

the same cell on the same fr equency at the same time by exploiti ng the

spatial domain


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6-Applications of SA

Remote sensing Medical imaging

Mobile communication

A base-station with

cir cular adaptive

antenna arrays

Sat. communication/navigation


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Application on angle of arr ival

(AOA)


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Improved system capacities

H igher permissible signal bandwidths

Space division multiple access (SDMA)

Higher signal-to-interference ratios

I ncreased frequency reuse

Sidelobe canceling or null steer ing

Mul tipath mitigation

Constant modulus restoration to phase modulated signals

Blind adaptation

I mproved angle-of-arr ival estimation and direction f inding

I nstantaneous tracking of moving sources

Reduced speckle in radar imagingClutter suppression

I ncreased degrees of freedom

Improved array resolution

M IMO compatibil ity in both communications and radar

7-Potential benef its of SA


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There transceivers are much more complex than traditional

base station

The antenna needs separate transceiver chains for each

arr ay antenna element and accurate real-time calibration

for each of them

The antenna beam forming is computationally in tensive,

i .e., smar t antenna base stations must be equipped with very

powerful digi tal signal processors

Th is leads to increase the system costs in shor t term, but since the benefi ts

outweigh the costs, it wil l be less expensive in long run

8- Drawbacks of SA


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Summary

Adaptive Signal Processor:The weights are continuously adjusted bythe adaptive signal processor in order to

achieve the input function

Antenna Array:antenna elements are assumed to be identical wi th an

omnidirectional pattern in the azimuthally plane

Complex Weights:they adjust the ampli tude and phase of the signal

Since the main components of SA (AA) System are

We should study the following

A revision on arrays and phased arr ays

Narr owband and wideband beamforming ( traditi onal beamforming)

Adaptive beamforming (adaptive signal processing)


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References

1. Van Atta, L. Electromagnetic Reflection, U.S. Patent 2908002, Oct. 6, 1959.

2. Howells, P. Intermediate Frequency Sidelobe Canceller, U.S. Patent 3202990, Aug. 24, 1965.

3. Howells, P. Explorations in Fixed and Adaptive Resolution at GE and SURC, IEEE Transactions on Antenna and

Propagation, Special I ssue on Adaptive An tennas,Vol. AP-24, No. 5, pp. 575584, Sept. 1976.

4. Brock, D.K., O.A. Mukhanov, and J. Rosa, Superconductor Digital RF Devel opmentfor Software Radio, IEEE Commun.

Mag., pp. 174, Feb. 2001.

5. Li berti , J., and T. Rappaport, Smart An tennas for Wi reless Communi cations: IS-95 and Thi rd Generation CDMA Applications,

Prenti ce Hall New York , 1999.

6. Reed, J., Software Radio: A M odern Approach to Radio Engineer ing, Prentice Hall , New York, 2002.

7. Mitola, J., Software Radios, IEEE Commun. Mag., May 1995.

8. Doufexi, A., S. Armour, A. Nix, P. Karlsson, and D. Bull, Range and ThroughputEnhancement of Wireless Local

AreaNetworks Using Smart Sectorised Antennas, IEEE Transactions on Wireless Communications, Vol. 3, No. 5, pp. 14371443,

Sept. 2004.

9. Weisman, C., The Essential Guide to RF andWireless, 2d ed., Prentice Hal l, New York 2002.

10. Stall ings, W., Local and Metropoli tan Area Networks, 6th ed., Prentice Hal l, New York , 2000.

11. Skolni k, M., Intr oduction to Radar Systems, McGraw-H il l, 3d ed., New York , 2001.

12. Skolnik, M., Attributes of the Ubiquitous Phased Array Radar, IEEE Phased Array Systems and Technology Symposium,

Boston, MA, Oct. 1417, 2003.

13. Lal, D., T. Joshi, and D. Agrawal, Localized Transmission Scheduling for Spatial Multiplexing Using Smart Antennas in

Wireless Adhoc Networks, 13th IEEE Workshop on Local and Metropolitan A rea Networks, pp. 175180, Apri l 2004.14. Wang Y., and H. Scheving, Adaptive Arrays for High Rate Data Communications, 48th IEEE Vehicul ar Technology

Conf erence, Vol. 2, pp. 10291033, May 1998.

15. Jeng, S., and H. Lin, Smart Antenna System and Its Application in Low-Earth-Orbit Satellite Communication Systems,

I EE Proceedings on M icrowaves, Antennas, and Propagation, Vol. 146, No. 2, pp. 125130, Apri l 1999.

16. Dur gin, G., Space-Time Wireless Channels, Prenti ce Hall , New York, 2003.

17. Ertan, S., H. Griffiths, M. Wicks, et al., Bistatic Radar Denial by Spatial Waveform Diversity, IEE RADAR 2002,

Edinburgh, pp. 1721, Oct. 1517, 2002.

18-C.A. Balanis Antenna theory analysis and design, John Wiley and Sons


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