Design of Smart Antenna Testbed Prototype
R.K. Shevgaonkar,
R.S. Kawitkar,
Professor in Electrical Engg, Dept.,
Indian Institute of Technology Bombay,
Mumbai-400 076, (M.S.), India
+91-22-25767495
Electronics Engg., Dept.,
S.S.G.M. College of Engineering,
Shegaon44 203, (M.S.). India
+91-7265-252402
[email protected]
[email protected]
ABSTRACT
Keywords
The use of wireless, mobile, a personal communications setvice is
expanding rapidly. Market projections indicate that within ten
years approximately 50Uf the total teletraEc (including voice,
FAX and multimedia data) will be handled via mobile
communication networks.
Smart antenna system, digital signal processing, continuous wave,
digital audiotape, smart antenna m a y testbed.
Adaptive or ~ k ~ ~ t e arrays
n n acan further increase channel
capacity through spatial division. Adaptive antennas an also
track mobile users, improving both signal range and quality. For
these reasons, smart antenna systems have attracted widespread
interest in the telecommunications industry for. applications to
third generation wireless systems. The problems in 3G systems
can be effectively tackled by using smart antennas.
1. INTRODUCTION
In recent years, the limitationsof broadcast antenna technology on
the quality, capacity, and covepge of wireless systems have
prompted an evolution in the fundamental design and role of the
antenna in a wireless system. How can an antenna be made
intelligent?First, adding more elements can modify its physical
Second, the antenna can become an antenna system that
designed to shift signals before transmission at each of the
successiveelements so that the antenna has a composite effect [7].
This paper aims to design and develop an advanced antennas
testbed to serve as a common reference for testing adaptive
antenna mays and signal combining algorithms, as well as
complete systems.
The advent of powerful low-cost digital signal processors (DSPs),
general-purpose processors (and ASICs), as well as innovative
software-based signal-processing techniques (algorithms) bas
made intelligent antennas practical for cellular communications
systems [9].
The goal of this paper is to develop low complexity smart antenna
structures for 3G systems. The emphasis will be laid on ease of
implementation in a multichannel /multi -user environment. A
smart antenna test bed will be developed, and various stateof-theart DSP structures and algorithms will be investigated.
In the context of smart antennas, the term Wenna"has an
Some of the benefits that can be achieved by using SAS (Smart
Antenna System) include lower mobile terminal power
consumption, range extension, IS1 reduction, lngher data rate
support, and ease of integration into the existing base station
system. In terms of economic benefits, adaptive antenna systems
employed at base station, though increases the per base station
cost, can increase coverage area of each cell site, thereby reducing
the total sylem cost dramatically - often by more than 50%
without conrpromising the system performance. The testbed can
be employed to illustrate enhancement of system capacity and
service quality in wireless communications applications.
1.1 What is a Smart Antenna?
extended meaning. Fig.] shows the block diagram of Smart
Antenna System.
A
*WW
:t
Fig. 1. SAS block diagram
It consists of a number of radiating elements, a
combininaviding network and a wntrol unit. The control unit
can be called the smart antennab intelligence, normally realized
using a DSP. The processor controls feeder panmeters of the
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antenna, based on several inputs, in order to optimize the
communications link. This shows that smart antennas are more
than just the btenna,”but rather a complete transceiver concept
[l]. One may wonder why is it necessary to invest time and
money into such an idea, what was wrong with the current use of
the cellular mitennas?
In truth, antennas are not smart-antenna systems are smart.
Generally co-located &th a base station, a smart antenna system
combines an antenna array with a digital signal-processing
capability to transmit and receive in an adaptive, spatially
sensitive manner. In other words, such a system can automatically
change the directionality of its radiation patte,ms in response to its
signal environnient [XI.One should say that their matts reside in
their digital signal-processing facilities.
Smart miteiuia not only combats multipath fading, but also
suppresses interference signals. It employs Diversity and
Adaptive combining schemes. SA techniques have been
considered niostly for the base stations so far because of high
svstan complexity and high power consumption. Recently, matt
antenna techniques have been applied to mobile stations or
handsets (21.
The following are distinctions between the two major categories
of smart antennas regarding the choices in transmit strategy:
1 , Switched beam-A finite number of fixed, predefmed
patterns or combining strategies(sectors).
2. Adaptive array-An infmite number of patterns (scenaiobased) that are adjusted in real time.
Adaptive beamforming requires sophisticated signal processnig,
which until today was considered too expensive for commercial
application. The cost of processing has immensely reduced,
making beamforming relevant to the commercial market as a cost
effective solution for wide-scale deployment of broadband
wireless networks. With digital beamforming in a wireless
communication system, the received signals must be available as
complex digital data. Therefore a radio receiver must convert the
‘received RF signals to &gital baseband signals, for every antenna
[61.
This paper aims to design and develop a Smart Antenna Testbed
Prototype to seme as a common reference for testing adaptive
antenna arrays and signal combining algoritbnis, as well as
complete systems.
2. TESTBED IMPLEMENTATION
2.1 System Overview
A high-level block diagram of the Smart Antemia Anay Testbed
(SAAT) is shown in Fig. 3. It operates at 2.05 GHz. Continuous
wave (CW) signals are transmitted from one or two transmitters.
Data are collected using either a two- or a four-channel portable
receiver sysem [lo]. The data are analyzed o f f line to allow
comparison of different comhiiung techniques.
77
Pp
Handset
Receivers
Transrritter
IF iinals
1.2 Adaptive Beamforming
An adaptive beamformer is able to automatically update the
weight rec!or, in order to separate desired signals from interfering
signals. Adaptive beamfomiing can be done in many ways. Many
algorithms exist for many applications, varying in complexity [4].
It is accomplished using sofhvare and advanced signal processing.
The techiology conibines the inputs of multiple antennas (from an
anteiuia amy) to form very narrow beams toward individual usen
inacell [13].
A generic adaptive beamformer is shown in Fig. 2. The weight
vector II’ is calculated using the signal x@J received by multiple
antennas. An adaptive processor will minimize the error e(t)
benveen a desired signal d(t) and the array output y@J.
Piocessoi
SINR in. SINR wt
received signal strength.
demodulated signal
Fig. 3. High-level block diagram of the SAAT
2.2 Transmitters
$1
+
=+fs
// lel ’
”’’
The testbed uses one or two transmitters. For diversity
nieasurements only one of the transmitters is used. Both
transmitters are used when interference reiection iiieasurenicnts
are performed to evaluate adaptive beamforming perfonnance.
Either source can he considered as bmmitting the desired signal.
The other source is then an interfering signal.
The transmitters use the archtecture depicted in Fig. 4. The
transmitters are typically mounted on tripods and operate from
fixed positions hut are transportable and run 011 batteries for use in
the field. Additional transmitters can he added as needed. The
transmitters transmit CW signals at 2.05 GHz 151. About 1 Wz
offsets the transmitter frequencies so that the signals can be
distinguished, and both signals fall within the bandwidth of the
receiver unit.
Fig. 2. Concept of the adaptive beamforming.
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I bW
lucked
multiplier
Fig. 4. Block dmgram of a SAAT transmitter
2.3 Two -Channel Handheld Receiver Unit and
Data Logger
Fig. 5 shows the two-channel receiverdata logger and data
processing system. The handheld receiver unit consists of a box
having the approximate size and shape of a handheld radio and
includes antmias, receivers, and a portable digital audiotape
(DAT) recorder (a Sony TCD-DS), used to log data. Two
antennas, each connected to a separate receiver, are mounted on
the box. The receiver IF outputs are connected to the DAT
Fig. 6. Receiver architecture block diagram
2.4 Data Processing Hardware
The SAAT data processing system is used to analyze the collected
data. The system consists of a computer with an interface to the
data logger and software that determines statistics of the collected
data and can be used to determine the performance of different
combining techniques for each antenna configuration tested [lo].
The system uses a 450 M H z Pentinm computa with 256 MB of
RAM that rnns Windows NT 4.0 Workstation.
2.4.1 Testbed Experiment
The testbed system is designed to perform experiments in which
the transmitting nnit(s), could be mobile or stationary, transmit
continuously, while antenna array receiver system records data U1
bursts of programmable duration at a programmable duty cycle
151-
2.6 Testbed Software
A flexible suite of off-line processing software is witten using
MATLAB to perform system calibration, testbed initialization,
data acquisition control, data storageiransfer, off -line signal
processing aid analysis, and graph plotting. Another set of
software is written in C for real-time data'acquisition, signal
processing, data analysis and graph plotting [ I I].
Fig. 5. Blocl\ diagram two-channel receiverdata logger and
data processing system
The entire receiver unit is portable so that an operator can carry it,
and is rugged enough that it can he used to perform experiments
in a wide variety of locations and conditions.
Fig. 6 . shows the receiver and data logger. The received RF
signals are mixed down to baseband and recorded on the two
channels of a DAT recorder. The recorder is capable of recording
at 32,000,44,100, and 48.000 sainoles ner second for a maximum
24 kHz bandwidth
The reason for choosing hilitlab environment to realize the beam
tracking and searching algorithm is to simplify the software
development [13]. With hundreds of math, scientific and
engineering functions, Matlab programming environment
integrates high performance computation, visualization and
specific application toolboxes, such as signal processing and
neural network toolboxes, and makes it possible to improve the
beam-control application to a higher level of sophistication.
The software is responsible for acquiring, processing, and
recording received signals and displaying measurement .or
algorithm results [12].
The softwarehas evolved to include the following modules:
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.
.
Antenna diversity and diversity gain processing
Measurement of time dispersion chmct&tics
(multipath) of radio channels
~ ~ ~ l ~of smart
~ tantenna
a t algorithms
i ~ ~developed
inMATLAB
Power, time -domaiq and spectrum measurement
Acquisition and recordmg of raw received signals
Playback of recorded signals for developing and testing
new algorithms
BENEFITS OF SMART ANTENNA
TESTBED PROTOTYPE
3.
Increasedcoverage,
9 Improved link quality,
Increased capacity,
9 Increased data rate,
Higher sensitive reception,
Reduced costs and increased return on investment,
Lower handset power consumption,
P Assistance in user location by means of direction fmding,
9 Can provide multipath dispersion, interference suppression,
9 Confine the broadcast energy to a narrow beam.
9 Conventional antennas cause coupling of the hand and head
hut adaptive antennas do nd cause coupling of the hand and
the head,
9 There is lower specific absolptionrate ( S A R ) ,
9 Mitigation against dead zones around Base stations of
adjacent channel FDD network operators [I],
9 Improved spectralefficiency,
9 It is possible to combine the signals from the antennas in a
particular way that both the S N R (signal to noise ratio) and
CIR (carrier to interference ratio) levels are improved,
9 CO-channel interference reduced by applying antenna
diversity at the handset,
9 The possibility to implement systems with SDMA,
9 Reduction of multi- path f a ;
> Improvements of call reliability;
9
9
9
9
9
,
3.1 Cost Factors
Although the benefits of using smart antennas are many, there are
also drawbacks and cost factors. The gain should always be
evaluated against the cost [6]. SA increases system complexity
and costs, but at the Same time provides an additional degree of
freedom for the radio network control and planning.
4. CONCLUSION
software development environment. The real-time operating
system enables evaluation of the behavior of digital algorithms
and real-world systems [14]. The test-bed demonstrates proper
operation of the CM algorithm used for digital beamforming,
combined with digital down conversion.
While Smart antenna systems are a promising solution for an
upgrade to cellularFCS system performance, their development
for CDMA applications are still in a ~ d i m e n t t ~ ‘phase.
y
No
products are available on the market, and no vendors have
announced the prototype availability.Why is this so?
5. ACKNOWLEDGEMENT:
Tke author is deeply grateful to Hon. Shrikant Patil (Director),
and Hon. Dr D.G.Wakde (Principal), S.S.G.M.College of
Engineering Shegaon for their kmd encouragement and help
during the progress of this work.
6. REFERENCES
[ l ] B. Widrow, P.E. Mantey, L.J. Gnftiths, B.B. Goode,
“‘Adaptive A n t e m Systems:’ Proc IEEE, Vol. 55, No.12,
December 1967, pp.2143-2159.
[2] J. H. Winters, Signal Acquisition and Tracking with
Adaptive Arrays in Wireless Systems”, IEEE Trans. Or
Vehicular Technologp,November 1993, pp. 377 - 384.
[3] L.C. Godam, “Application of Antenna Arrays to Mobile
Communications, Part 11: Beam-Forming and Direction of
Arrival Considerations’,’ Proc. FEE, Vol85, No. 8, August
1997,pp. 1195-1245.
[4] M. Barrett and R. Amott, Adaptive Antennas for Mobile
Communications,”Elechonics
and
Communications
Engineering J o u m l , Aug. 1994, pp. 20314.
[SI P. Mogensen et al., A Hardware Testbed for Evaluation of
Adaptive Antennas in GSMUMTS,” 7th IEEE Inr’l. Symp.
Pers.. Indoor and Mobile Radio Commun. P M C P6,
Taipei, Taiwa& Oct. 1518, 1996, pp.54044.
[(;I P.M. Grant, J.S. Thompson and B. Mulgrew, ‘‘ Adaptive
Arrays for Narrowband CDMA base stations:’ Elecponics &
Communication Engineering J a m ” . August 1998, pp. 1%.
[7] R.S.€&itkar,
l’ntntepolation of electric -field values in
frequency and space in the analysis of printed dipo1es:proc.
of national conference on application of Fourier and wavelet
analysis in engineering and technologv,
_.. Chikballauur.
. .India.
Mai1999,ppr24
181 R.S.lhKitkar. “Calculation of mtial sienatures in snmi
antenna systems:’ proc.of National conf. on integral
transforms &heir applications in science dtngg, SSGMCE
Shegaon,India, 16-18 Feh.2002,pp.l31
[9] S. Ponnekanti, “An Overview of Smart Antenn a Technology
for Heterogeneous Networks’,’ IEEE Commun. Sulveys, Vol.
2, No. 4, Fourth Quarter 1999, pp. 14-23.
[IO] T. Biedka et al., l’mplementation of a Prototype Smart
Antenna for Low Tier PCS,” Proc. 49th IEEE Vehic. Tech.
ConJ W C Y 9 Spring, Houston,TWSA,May 1999,pp.l6 .
[I I] Texas Instnunents, Designing With the THS1206 High speed Data Converte?,’April2000.
[12] Texas Instruments, TMS320C6000 Peripherals Reference
Guide’,’Fehtuaty 2001.
[I31 T. Ewer, “Development of a Smart Antenna Test -bed,
Using Digital Beamformingy University of Twente, M.Sc.
Thesis, 2001.
[ 141 hnp://www.metawwe.com/Ci,stome~/casesfudhtm
[ 151 h n p : / ~ . m y t h e o n . c o m t a n t . h t m
L
Smart antenna technology is a broad concept and implementations
range from simple techniques that involve switchmg between
lobes to advanced algorithms maximizing the received signal-tointerference ratio. The choice of a SA receiver and algorithm
today is highly dependent on the air interface and its parameters.
To improve radio network performance, SA receiver structure and
algorithms should be optimized according to the propagation and
interference environment, considering expected W i c and users
mobility in the cell [7]. These parameters can be seen as a product
of radio network planning. At the Same time, SA receiver
parameters are important for capacity, coverage and interference
planning, they also tightly interact with network control protocols
at different layers.
To be able to test algorithms and systems for wireless
communications in general and smart antennas in particular, a
flexible Smart Antenna test-bed is designed. The test-bed was
formed by general-purpose hardware, combined with a flexible
1
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