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Standardization and System integration of Smart Antennas intoWireless Networks. Adrian Boukalov Helsinki University of Technology Communications Lab ETSI/MESA meeting 18.09.2001 firstname.lastname@example.org. Content. 1.Smart antennas. Benefactors. Operators perspective. User perspective.
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Helsinki University of Technology
1.Smart antennas. Benefactors. Operators perspective. User perspective.
2. Overview of communication systems with Smart Antennas (SA).
3. Basics of Smart Antennas Techniques. SA types, classification.
4. Integrated receiver design with SA.
5. Impact of mobility, propagation environment and interference on
SA applicability and performance.
6. Air interface spec and SA compatibility/performance.Standardization related issues
7. Wireless network performance and planning with SA.
8. Current status and future evolution of SA techniques.
9. SA system integration: Problems Solutions
10. SA system integration research at ComLab/HUT
There are very few techniques proposed
today, which are able to improve radio network
- Spatial processing
- Multi-user detection
- Channel reuse based on polarization
- Advanced network control
Spatial processing is among them and can be
effectively combined with others techniques
How smart should be Smart Antennas techniques ?
Network capacity, coverage, less
internetwork interference, filling
“dead spots”, fewer BSs,QoS, new
New market for more advanced BSs,
flexible radio network control...
Higher QoS, more reliable, secure
communication, new services,
longer battery life...
Link level improvements System improvements
- Interference cancellation at the up and down links
- SNR improvement
due to antenna gain
- Multipath mitigation
Quality of service
(QoS), bit rate,
- A. BS only
&down-link…..…coverage + capacity, spectrum efficiency due to
reuse: between cells (SFIR),due to reuse
inside cell (SDMA), both SDMA+SFIR
- B. MS/subscriber only
up-link……………capacity/. due to the tighter channel reuse
&down-link……....coverage (WLL applications)
- C. Both ends
MS and BS
simultaneously…..coverage + capacity (A+B) + higher bit rate
up-link & due to spatially multiplexed parallel channels and
down-link split high bit rate data streams between them or
.....higher transmission quality with ST coded
Communications on the Globe
- installations in WLL
- tests for GSM 1800
Ericsson (SW) first system
system solution with SA GSM
Radio Design AB (SW)
Testbed for UTRA
“ IntelliWave” Wireless Local Loop System
Adaptive Smart Antenna System
TSUNAMI-SUNBEAM-SATURN/METRA Projects (EU)
- Wide range of R&D activity
ARPA (USA )/GloMo project
- Recommendations for standardization
- Field Trials GSM/DCS 1800 system
Motorola European Cellular Infrastructure Division UK
Switched Beam System
France Telecom CNET France
University of Aalborg Denmark
Bosch Telecom GmbH Germany
Orange Personal Communication Systems Ltd. UK
University of Bristol UK
Polytechnic University of Catalonia Spain
- Improvement in SNR due to beamforming/combining array gain. (Improved coverage. )
- Reduced ISI.
- Enhanced spatial diversity. Path diversity.
- Interference cancellation. In Trx. and Rx. Capacity.
=> Improved transmission rate with link adaptation techniques.
These goals may be conflicting. Need balancing to achieve
synergy with propagation environment, offered traffic, infrastructure !
- Macro-diversity with:
* Combining (MRC,IRC,OC)
(Trx. Coding, V-BLAST,...)
- Beamforming (BF)
Switched-beam Smart Antenna
These approaches can be/should
be applied together !
- Gain=10 log M (M-number of
- directional BF or switched BF can
add 10-12 dB to link budget
- can be controlled dynamically
- Multi-path => diversity combining
and/or matched beamforming.
More complex algorithms.
- BF + combining techniques
System level improvements=>
- increased coverage
- possible reduction amount of BS
- Penetration into buildings....
Reduction of the number
of BS sites with HSR
Range extension factor
BS reduction factor
Range extension with HSR
0 5 10 15 20
Number of elements
- Spatial diversity combining techniques:
Selection diversity, equal gain combining,
Maximum Ratio (MRC),...
- Spatial diversity requires 10 - 20 wavelength
- Path diversity. Paths identification problem.
- Combinations with other diversity techniques.
polarization, frequency,..modulation diversity
in multicast transmission
System level improvements=>
- More reliable communication
- Higher Bit Rate
- Reduced power consumption for PC systems
- might improve capacity in 3- 8 times
- might require more complex algorithms in
- Combinations with other interference
* Multi-user detection (knowledge of other
users waveforms, adaptive)
* Power control
* Error correction coding
* Temporal domain interference cancellation is
* network control based techniques
- IC is more important in cellular networks (GSM,3GPP)
System level improvements=>
- higher spectrum efficiency/capacity
- can be translated to higher BER due to higher SIR or with more ch.
- antijamming possibilities
Spectrum efficiency gain of SFIR
Spectrum efficiency gain of SDMA
- N= M-1
… - N= M/2
- 25% load, optimized
--- 50% load , optimized
0 5 10 15 20
0 5 10 15 20
Number of elements
Number of elements
M -number of array elements
N - number of parallel beams
- spatial domain - only interference
cancellation is possible
- preferably to combine with temporal
(preserves signal energy, diversity,more
- decoupled/joint space time processing
- ZF, MMSE, MLSE joint/decoupled S-T
System level improvements=>
- Higher BER
- Improved reliability
- Improved performance in Multipath
~1/M (M-1) ~M ang. div (M-1)
(M-1) M spat div. (M-1)/2
interferers gain del. symb.
Degrees of freedom number of SA elements
- Number of SA elements (M)
can be considered as a
“resource”, i.e. degrees of
freedom which can be spent
for SNR, CCI, diversity, ISI,
either separately or jointly
- M determines “spatial selectivity” of SA
=> Integrated transceiver design
- Based on cost function maximization/minimization
(max SINR,…)-> difficult to obtain in practice
- Based on Statistical Estimation. MAP.
ML (Likelihood function)-> treats interference as temporally and spatially white Gaussian. Balance effect of noise. Complexity.
MSE -> more attractive in presence of correlated CCI. ZF force could not balance effect of noise.
MMSE partly solves this problem. Algorithms complexity spectrum efficiency. Blind methods.
- Spatial reference based BF-direction of arrival
based beamforming (DoABF)
Spatial Eigenstructure based BF
- Reference signal based/time reference BF
(TRB) and/or optimum combining (OC) ,
MMSE in BF and channel est. S-T processing
- Signal structure (temporal /spectral) based
beamforming, SSBF/property restored BF
blind methods , MSE-like BF and ch. est in STP
- Blind - Decision Directed (DD) techniques
- require angle of arrival (AoA)
- estimates output power at the output or input correlation matrix
- sensitive to AoA estimation errors, calibration problem
- problem with coherent multipath
- Angular spread to
array resolution ratio should be low
- FDD applications
- some methods of AoA estimation might be problematic in CDMA
Time-Reference Signal Based Beamformers and/or optimal combiner (TRB)
- requires reference signal or the replica
correlated with desired signal
- reference signal multiplexed with
desired signal or reconstructed
from detected symbols
- better for varying radio channel
- provide diversity
- may be more processing extensive
- receiver is simpler at expense spectral
- synchronization problem
- Delay spread (Ds) to frame length (T)
ratio should be low
- TDD applications
- Does not require reference signal,
thus increase spectral efficiency
- constant modulus (CM)property of
phase modulated signals,
- finite alphabet (FA) property of
digitally modulated signals ,
- spectral coherence restoral SCORE
(only information needed - bit rate)
- useful method for tracking
between references intervals
- convergence properties ?
- methods based on partial
information are usually non-linear
- performance from robustness
point of view similar to reference
signal based methods, DD technique
- better perform in environments with low angular spread
- require AoA estimation and calibration
- can work in higher Doppler spread
- feasible with FDD applications
- macrocell environment
TRB or/and OC (Blind Algorithms)
- well perform in environments with high angular spread
- require reference signal (spectrum efficiency), synchronization
- well suit for TDD (micro/pico cells), FDD is more problematic
micro and picocell
- temporal structure based algorithms can better handledelay spread, but higher speed can be problem
- more robust methods in changing environment (adaptive algorithms)
- Spatial multiplexing=>Data Rate
- Layered Architecture (BLAST)
- ST Coding => Diversity=>BER
- Mutiplexing or Diversity ?
- MIMO CDMA with SA
- Iterated receiver design
multiple antennas at MS
Time domain processing
(Equalization, RAKE, …)
Channel and ST coding
- Integrated Temporal Spatial
Frequency domains receiver
- More coupled with detection (DD,
Joint Channel est.)
- Integrated with MUD/IC
- Integrated with coding
- propagation environment=> spreading in space-time, fading
- interference environment
B. System parameters/air interface type
C. Operator requirements/services requirements
Smart Ant. Tech.
- Capacity, coverage, interference
- Joint fixed and radio network
- System upgrade, economical issues
1G- analog systems
2G- digital systems
2.5G- digital+packet +.. (GPRS,..)
3G - W-CDMA
4G- cellular+ gigabit WLAN
Tx, Rx algorithms
- Spatial proc.
- Time domain proc.
Services -> MS location
- R.resource management
- call control
- admission control
- broadcast channel control
- handover control
- macro-diversity control
- Multiple access
- Availability of pilots
Link level control
- Power Control
- Quality Control
- Smart Antennas algorithms should be optimized according to
the propagation environment based on the cell by cell principle
Antennas elements geometry,
numbers of elements - M.
Radio Transmission Technologies
of the training
band SA rec,
BF, AoA est
- In non-multiuser case users are seen as interference to each other and there are many weaker CCI in the uplink. Capacity is improved due to reduction of TRX power - Multipath gives rise to the MAI due to the losses of codes orthogonality. Can be improved with SA. - Code can be seen as a “free” reference signal - Wideband beamforming realization and methods of AoA estimation are different from narrowband - Channel estimations can be based on spreading codes and it presumes introduction of novel techniques- Narrowband systems are more feasible with SA.....(coherence nature of array processing)
- M degrees of freedom should be carefully spent according to the expected propagation and interference environment taking into consideration availability of other techniques(interference cancellation,diversity,..)
- Environment (spreading) “complexity” <=> receiver and algorithmic complexity
(How modelling in algorithms corresponds to reality ?)
Smart Antennas might be not very smart (Complexity)
Integrated but relatively simple system design can provide considerable improvement with low level of complexity
1. High Sensitivity Reception (HSR)
2. Spatial Filtering for Interference Reduction (SFIR)
3. Space Division Multiple Access (SDMA)
- CCI cancellation + SA at the down-link
- capacity improvement of 2.5 require 6dB
CIR improvement (already achieved by
Ericsson with simple SA algorithms)
- the same range extension as with HSR
- simulations shows that approximately the
same capacity gain can be achieved with
SFIR and SDMA while SFIR require
considerable less network control upgrade
- it was found reasonable to combine in
GSM SFIR with random slow
frequency hopping to benefit from
interference and frequency diversity
- reuse factor 1/3 seems reasonable
1/1 possible but too complex since
dynamic RR management based on
CCI measurements is required
- frequency re-planning, but network control (RR) less affected
- expected up to 8 times capacity improvement
- power classes concept (can be dynamic
- with ref. signal BF MSs can be
separated even when they have the
same angular position to BS !
- for DoABF MSs angular distribution
is important (macrocell)
- network planning (frequency) is simpler,
but larger cell size can require new planning,
more smooth migration into existing network
- more network management upgrade required
combined with user specific info
Initial access , HO control
Reference signal availability
Multiple Access ,
Broadcast channels control
- power control at up and down links is beneficial
(60% more capacity ) (Downlink in SDMA can be problematic
due to furthest mobile)
- dynamic behavior of tracking & power control ?
- user identification problem to support SDMA
individual color codes needed to support each SDMA
traffic channel channel, also for admission control ..
- for “rescue” purposes omni directional channel for call recovery
- power classes concept (SDMA, others ..? )< -->RR
management( tradeoff needed to avoid trunking effects)
BSLayer 2. Initial access. Handover.
- location aware HO or through
omni-directional channel ?
- initial access with omni directional
channel=> narrow beam or
transition wide beam =>narrow beam
- to setup beamformer just before
user dedicated channel is allocated
(access procedure modification or
increased access time )
- delayed handover while new BS has not been localized
- how to make down-link BF when channel info. at the up-link is not
available yet (temporal omnidirectional downlink or longer access)?
- to allow different synchronization sequences
- packet capturing by SA can improve packet transmission via
random access channel
- new functions: physical channel allocation based on angular information and or link quality monitoring
- dynamic channel allocation (DCA)
(localization with different precision... ?? needed)
=> precise localization - centralized DCA or
=> no DCA with SFIR and interference averaging approach or
=> subdivision on sectors and create list of forbidden sectors
- joint power control , beamforming and BS assignment
- centralized or distributed control (bunch concept) ?
- smoothing of spatial traffic distribution
- more benefit we expect to get (capacity,flexibility)- more RR management should be aware of spatial characteristics
revolving beam concept in TDMA
(more feasible for coverage extension)
neighboring cell monitoring can be
more problematic . Frame structure...
- Adaptation to traffic variations
Traffic control cell coverage by reshaping
transmitted antenna pattern
(sectorized and non-sectorized)
- Network Planning
need to split carefully beamformed
and omni-directional channels …..
New service (991, transport control…)
Combined DOA measurements and time delay based
Raytheon introduced commercial available geolocation
system (SA option is included)
- More benefits with SA- > more :
Resource management should be aware of:
- > User location (AoA,..)and/or
- > Power (power classes ,...)and/or
- > Channel quality (and spatial properties ?)
Co-ordination between BSs
-> at least loose form of synchronization for time reference BF
-> exchange information about user location and /or
- > channel quality (and spatial properties ?)
-> exchange information about cells traffic load
channels (user dedicated pilots, color codes, different
synchronization sequences) to separate/identify users
(implemented in new air interfaces cdma- 2000,UTRA)
- Channels structure should be more carefully divided between
beamformed and omnidierctional.
Minimize blanket coverage in terms of frequency/time
- DTX(comfort level?), HO, initial protocol perhaps should be
slightly modified,but it can increase signaling overhead=>
more interference in CDMA
- combination with link adaptation (since at the beginning
“channel history” is not available). This combination will
increase “soft capacity limit”
- some changes can be expected at the MS (receiver, ant., protocols)Network issues => Standardization
- Integrated receiver design with SA
- MIMO system (CDMA/3G)
- Joint Spatial Domain Processing =>....
- Advanced Simulation Tool Development.
Parallel Computing- Programming
System<=>Signal Level Simulation.
3S Simulator (Signal, System, Services)
Center of Helsinki
- incoming impulses from the MS1 - amplitude and AOA
- incoming impulses from
the MS2 - amplitude and AOA,
considered as “interference”
for MS1 (and vs)
- Smart Antenna’s radiation pattern antenna main lobe locked on the signals coming from MS1
Smart Antennas Model
- Basic research on applicability/optimization of SA techniques
taking into consideration TETRA system
- Performance with different SA techniques and receivers
structures. Coverage, BER,..
- Achievable improvement with SA and link adaptation techniques
- Transceiver complexity study
- Performance in multi-service environment(simulation)
- SA at the MS/vehicle as a relaying platform
1.Edward Mutafungwa, Lauri Halme, Viktor Nässi, Adrian Boukalov “A study of the Järvenpää-Lahti motorway's IT link
alternatives for the connection of control stations”, Espoo, Otaniemi: TKK Tietoliikennelaboratorio technology reports, 1998.
2. Adrian Boukalov "The impact of a non-uniform spatial traffic distribution on the CDMA cellular networks system
parameters", URSI/Remote Sensing Club of Finland/IEEE XXIII Convention on Radio Science and Remote Sensing
Symposium, Otaniemi 24-25 August, 1998, Helsinki University of Technology Laboratory of Space tech. Report 35, p.29-30
3. Boukalov Adrian, Sven-Gustav Häggman and Antti Pietilä "The Impact of a Non-uniform Spatial Traffic Distribution on
the CDMA Cellular Network System Parameters", ICPWC'99, Jaipur, India, February 1999, pp. 394 -398.
4. Boukalov Adrian, Sven-Gustav Häggman "UMTS Radio Network Simulation with Smart Antennas ", Proceedings of the
Virginia Tech Symposium on Wireless Personal Communications, June 2-4, 1999, Blacksburg , USA , pp. 95-102.
5. Boukalov Adrian, "System Aspects of Smart Antennas Technology" Presentation at Radio Communication Systems
Department / School of Electrical Engineering and Information Technology (EIT) at the Royal Institute of Technology (KTH),
Stockholm, Sweden. Available at: http://www.s3.kth.se/radio/seminars/sa.pdf.
6. Boukalov Adrian, Sven-Gustav Häggman "An overview. System aspects of Smart Antennas Technology in Wireless
Communications" (Invited) , Proceedings of the 11th International Conference on Wireless Communications vol. 2,
12-14 July 1999 Calgary , Canada, pp.1-14.
7.Boukalov Adrian, Sven-Gustav Häggman " UMTS Radio Network Simulation with Smart Antennas" to be published in
book Wireless Personal Communications, Kluwer Academic Publishers, 2000.
8. Boukalov Adrian, Sven-Gustav Häggman "System Aspects of Smart Antennas Technology in Cellular Wireless
Communications " (Invited) IEEE Radio and Wireless Conference (RAWCON 99), Denver, Colorado, USA,
August 1-4, 1999, pp. 17-22.
9.Boukalov Adrian, "Introduction to Smart Antennas Techniques and Algorithms" Workshop on Smart Antennas
Technology and Applications at RAWCON 99, 1st August 1999.
10. Boukalov Adrian, Sven-Gustav Häggman “ System Aspects of Smart Antennas Technology in Wireless
Communications” to appear in Journal IEEE Transaction in Microwave Theory and Techniques
11. Boukalov Adrian, “Integration of Smart Antennas into Wireless Network” (Invited paper), book Global Wireless
Communications for World. Markets Research Centre's Business Briefing Series. Wireless Technology 2000.
(also see at http://www.comlab.hut.fi/thesispub.htm)