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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 adrian.boukalov@hut.fi. Content. 1.Smart antennas. Benefactors. Operators perspective. User perspective.

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standardization and system integration of smart antennas intowireless networks

Standardization and System integration of Smart Antennas intoWireless Networks

Adrian Boukalov

Helsinki University of Technology

Communications Lab

ETSI/MESA meeting

18.09.2001

adrian.boukalov@hut.fi

content
Content

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

slide3

"Spatial Processing remains as the most promising, if not the last frontier, in the evolution of multiple access systems" Andrew Viterbi

There are very few techniques proposed

today, which are able to improve radio network

performance dramatically

- 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 ?

smart antenna technology benfactors
Smart Antenna Technology: Benfactors

Network capacity, coverage, less

internetwork interference, filling

“dead spots”, fewer BSs,QoS, new

services...-> revenues

New market for more advanced BSs,

flexible radio network control...

Higher QoS, more reliable, secure

communication, new services,

longer battery life...

Operator

OEM

User

smart antenna technology motivation
Smart Antenna Technology:Motivation

Link level improvements System improvements

- Interference cancellation at the up and down links

- SNR improvement

due to antenna gain

- Multipath mitigation

capacity

coverage

Quality of service

(QoS), bit rate,

mobility rate

smart antennas might be used at
Smart Antennas might be used at:

- A. BS only

up-link…………..coverage (HSR)

&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

diversity

slide7

Smart Antennas in Mobile

Communications on the Globe

ArrayComm (USA)

- installations in WLL

- tests for GSM 1800

GigabitWireless(USA)

WLL

Ericsson (SW) first system

system solution with SA GSM

(commercially available)

Radio Design AB (SW)

NMT-450

NTT DoCoMo

(Japan)

Testbed for UTRA

“ IntelliWave” Wireless Local Loop System

Raytheon

(USA)

Commercially available

Fully

Adaptive Smart Antenna System

UMTS ?

TSUNAMI-SUNBEAM-SATURN/METRA Projects (EU)

- Wide range of R&D activity

ARPA (USA )/GloMo project

- Recommendations for standardization

Metawave

(USA)

- Field Trials GSM/DCS 1800 system

Commercially available

ERA Technology

Coordinator

(UK)

Participants:

IntelliCell

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

DETyCOM Spain

University of Bristol UK

Polytechnic University of Catalonia Spain

improvements achievable with spatial processing techniques
Improvements achievable with spatial processing techniques

- 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 !

spatial processing approaches
Spatial Processing Approaches

- Sectorization

- Macro-diversity with:

* Combining (MRC,IRC,OC)

* Prefiltering/Coding

(Trx. Coding, V-BLAST,...)

- Beamforming (BF)

Switched-beam Smart Antenna

Adaptive beamforming

These approaches can be/should

be applied together !

Sectorization

Macro-diversity

Switched-beam ant.

Adaptive BF

improved snr

SNR CCI Diversity ISI Time domain diversity

Improved SNR

Combining. MRC

Beamforming

=

BS

MS

Co-phased signals

weighted proportionally

to noise level/antenna

~1/M

Spatial domain

Signal Domain

improved snr due to sa antenna gain
Improved SNR due to SA antenna gain.

- Gain=10 log M (M-number of

antenna elements)

- 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

BF

Combiner

BF

System level improvements=>

- increased coverage

- possible reduction amount of BS

- Penetration into buildings....

improvements in system performance with sa
Improvements in system performance with SA

HSR

Reduction of the number

of BS sites with HSR

3.0

2.5

2.0

1.5

1.0

0.5

0.9

0.8

0.6

0.4

0.2

Range extension factor

BS reduction factor

Range extension with HSR

0 5 10 15 20

Number of elements

improved diversity space path

SNR CCI Diversity ISI Time domain diversity

Combining

Space Div.

Improved - diversity (space,path)

Beamforming

Multi-path

MS

BS

.Path. Div.

M

~M

improved diversity space path14
Improved - diversity (space,path)

- Spatial diversity combining techniques:

Selection diversity, equal gain combining,

Maximum Ratio (MRC),...

- Spatial diversity requires 10 - 20 wavelength

interelement spacing

- Path diversity. Paths identification problem.

- Combinations with other diversity techniques.

polarization, frequency,..modulation diversity

in multicast transmission

BF

Combiner

BF

Combiner

System level improvements=>

- More reliable communication

- Higher Bit Rate

- Reduced power consumption for PC systems

co channel interference cci cancellation

SNR CCI DiversityISI Time domain diversity

Co-Channel Interference (CCI) Cancellation

Beamforming

Combining

Interfering

MS 2

BS

MS 1

M-1 interferers cancellation.

independent of the propagation

environment

M-1

co channel interference cci cancellation16

BF

Co-Channel Interference (CCI) Cancellation

- might improve capacity in 3- 8 times

- might require more complex algorithms in

multipath

- Combinations with other interference

cancellation techniques:

* Multi-user detection (knowledge of other

users waveforms, adaptive)

* Power control

* Error correction coding

* Temporal domain interference cancellation is

limited (oversampling)v

* network control based techniques

- IC is more important in cellular networks (GSM,3GPP)

MUD

System level improvements=>

- higher spectrum efficiency/capacity

- can be translated to higher BER due to higher SIR or with more ch.

- antijamming possibilities

isi cancellation

SNR CCI Diversity ISI Time domain diversity

Delayed

Signals

Combining

ISI cancellation

Beamforming

Multipath

Path with ISI

BS

M-1

M-1 delayed signals cancellation

(M-1)/2 symbols due to delay spread

system performance improvement with sa
System performance improvement with SA

SFIR

SDMA

10.0

8.0

6.0

4.0

2.0

0.0

Spectrum efficiency gain of SFIR

25

20

15

10

5

0.0

Spectrum efficiency gain of SDMA

Efficiency gain

Efficiency gain

- N= M-1

… - N= M/2

.-..-.. N=4

- 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

isi cancellation19
ISI cancellation

- spatial domain - only interference

cancellation is possible

- preferably to combine with temporal

domain techniques

(preserves signal energy, diversity,more

efficient)

- decoupled/joint space time processing

- ZF, MMSE, MLSE joint/decoupled S-T

equalizers

BF

w

Equalizer

ZF,MMSE,

MLSE

BF

w

S-T Equalizer

ZF,MMSE,

MLSE

System level improvements=>

- Higher BER

- Improved reliability

- Improved performance in Multipath

optimal spatial algorithms

SNR CCI Diversity ISI Time domain diversity

Delayed

Signals

Combining

Optimal Spatial Algorithms

Beamforming

Multi-path

BS

Interfering

MS 2

MS 1

Path with ISI,

uncorrelated paths

optimal s t algorithms

SNR CCI Diversity ISI Time domain diversity

Delayed

Signals

Delayed

Signals

Time

Combining

Optimal S-T Algorithms

Beamforming

Equalisation

Multi-path

BS

+

Interfering

MS 2

MS 1

Path with ISI,

uncorrelated paths

Spatial domain processing Temporal domain processing

slide22

SNR CCI Diversity ISI

~1/M (M-1) ~M ang. div (M-1)

Optimum BF

(M-1) M spat div. (M-1)/2

interferers gain del. symb.

Optimum Combining

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

(optimum)

- M determines “spatial selectivity” of SA

=> Integrated transceiver design

st processing optimization criteria
ST processing. Optimization Criteria.

- 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 only and s t techniques classification by reference type
Spatial -only and S-T Techniques. Classification by Reference Type

- 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

direction of arrival based beamformers doabf
Direction of Arrival Based Beamformers (DoABF )

- require angle of arrival (AoA)

estimation

- 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

Array

Processor

Array

Output

slide26

Time-Reference Signal Based Beamformers and/or optimal combiner (TRB)

LS Beamformer

- 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

efficiency

- synchronization problem

- Delay spread (Ds) to frame length (T)

ratio should be low

- TDD applications

1

X1(t)

W1

Array

output

2

X2(t)

W2

y(t)

N

Xn(t)

Wn

Control

algorithm

Ref.

Error

-

+

Signal processor

+

Adaptive processor

signal structure based beamforming ssbf blind bf techniques
Signal Structure Based Beamforming (SSBF). Blind BF techniques.

- 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

BF

(W)

CMA

spatial processing summary
Spatial processing: Summary

DoABF

- 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)

mimo systems with sa at the ms bs
MIMO systems with SA at the MS& BS

Spatial multiplexing

- Spatial multiplexing=>Data Rate

- Layered Architecture (BLAST)

- ST Coding => Diversity=>BER

- Mutiplexing or Diversity ?

- M</>N

- Sub-arraying

- MIMO CDMA with SA

- Iterated receiver design

N

M

or

ST Coding

slide30

MIMO techniques<=> different propagation environment

WLL

MSC

LOS

Urban area

BS

BS

NLOS

Rural area

BS

MSC

multiple antennas at MS

possible combinations of spatial processing with other techniques
Possible combinations of spatial processing with other techniques

Time domain processing

(Equalization, RAKE, …)

Diversity (polarization,

additional macro,..)

Channel and ST coding

MU detection

Link adaptation…

Spatial processing

&

integrated receiver design with sa
Integrated Receiver Design with SA

Radio Channel

- Integrated Temporal Spatial

Frequency domains receiver

- More coupled with detection (DD,

Joint Channel est.)

- Integrated with MUD/IC

- Integrated with coding

Time

Doppler

Spatial

factors to be considered in sa system integration
Factors to be considered in SAsystem integration

A. Environment

- propagation environment=> spreading in space-time, fading

- interference environment

- mobility

B. System parameters/air interface type

C. Operator requirements/services requirements

slide34

SA Integration into Cellular Networks

Smart Ant. Tech.

Network Planning

- Capacity, coverage, interference

planning

- Joint fixed and radio network

optimization, planning

- System upgrade, economical issues

1G- analog systems

2G- digital systems

2.5G- digital+packet +.. (GPRS,..)

3G - W-CDMA

4G- cellular+ gigabit WLAN

Radio Interface

Receiver structure,

Tx, Rx algorithms

- Spatial proc.

- Time domain proc.

- Coding

- Detection

- Diversity

- ………..

Radio Network

Management

DSP

tech.

SW

Radio

Services -> MS location

Network control

- R.resource management

- call control

Cell control

- admission control

- broadcast channel control

- handover control

- macro-diversity control

1G

2G

Air Interface

- Multiple access

- Duplexing

- Modulation

- Framing

- Availability of pilots

2.5G

Link level control

- Power Control

- Quality Control

- Tracking

3G

4G

slide35

Macrocell and Microcell Channel Response

Macrocell

Microcell

Remote

scatters

1800

1800

Scatters

local to

BS

-1800

0

1

0

20

Delay (microsec)

Delay (microsec)

Scatters

local to

MS

After A.Paulraj

- Smart Antennas algorithms should be optimized according to

the propagation environment based on the cell by cell principle

slide36

Spatial Processing: Integration with Air Interface

Antennas elements geometry,

numbers of elements - M.

Radio Transmission Technologies

MS

Internetworking

Physical

Channel

Definition,

Multi-

plexing

Multiple

Access

Technology

Frame

Structure

Duplexing

Technology

RF- Channel

parameters

Modulation

Technology

Channel

Coding

Source

Coding

Availability

of the training

signal

Frame length

- T

Mapping

control,

traffic

channels

FDD

TDD

Modulation type

CM...

Finite Alphabet

Linearity

FDMA

CDMA

Combination

with Space

Processing

Bandwidth-B

Carrier

frequency fo

UL->DL

link

Wide/narrow

band SA rec,

BF, AoA est

Blind

methods

SSBF, ST

Ref.

Signal

based

BF, S-T

slide37

CDMA SA Receivers

- 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)

spatial processing summary38
Spatial processing: Summary

- 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 ?)

spatial processing summary39
Spatial processing: Summary
  • Best solutions: Combine trade-offs between:
    • - Beamforming <---> combining
    • - Algorithms (ML<---> MSE) , subspace
    • - Optimum <---> Data independent approaches
    • - Base band beamforming <---> RF/or IF beamforming
    • - Combination with other methods like multi-user detection (MUD), diversity, ST coding, adaptive modems
  • - Air interfaces should be not only “friendly” for S-T
  • processing but flexible / adaptive to be able to exploit
  • advantages of spatial processing in variable environments
  • - Integrated S-T MUD .... transceiver design...
spatial processing summary40
Spatial processing: Summary

Smart Antennas might be not very smart (Complexity)

Integrated but relatively simple system design can provide considerable improvement with low level of complexity

three stages of introduction smart antennas in cell planning process of 2 2 5 g networks
Three Stages of Introduction Smart Antennas in Cell Planning Process of 2-2.5 G Networks

1. High Sensitivity Reception (HSR)

2. Spatial Filtering for Interference Reduction (SFIR)

3. Space Division Multiple Access (SDMA)

hsr concept

BS

MS

HSR concept

- SA at the up-link only

- Gain approximately 10logM

- with 8 elements reduction of

number of BS by factor of 0.3

only by factor of 0.5 with diversity

- revolving beam technique improve coverage of BCH

sfir concept
SFIR concept

- 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

sfir concept44
SFIR concept

- 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

sdma concept
SDMA concept

- expected up to 8 times capacity improvement

- power classes concept (can be dynamic

or static)

- 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

PCH 1

PCH 1

PCH 1

PCH 1

impact on the network control
Impact on the network control

Geolocation

based on

AoA

estimation

Service

layer

RR management

interference averaging

U

C

Layer 3

DCA...,

combined with user specific info

*

*

(color codes,

AoA’s

)

Layer 2

*

Initial access , HO control

*

*

Reference signal availability

Layer 1

*

Multiple Access ,

Duplexing

,

PN, DTX.

*

*

Broadcast channels control

layer 1 power control quality monitoring tracking
Layer 1. Power control. Quality monitoring. Tracking.

- 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

is proposed

- power classes concept (SDMA, others ..? )< -->RR

management( tradeoff needed to avoid trunking effects)

layer 2 initial access handover

BS

BS

BS

Layer 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

Initial access

t

layer 3 resource management
Layer 3. Resource management.

- 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

broadcast channels control with sa
Broadcast channels control with SA

- Coverage

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 …..

network control with sa higher layers geolocation
Network Control with SA. Higher layers. Geolocation.

New service (991, transport control…)

Combined DOA measurements and time delay based

approach

Raytheon introduced commercial available geolocation

system (SA option is included)

network issues summary
Network issues. Summary

- 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

(Layer 1)

-> exchange information about user location and /or

- > channel quality (and spatial properties ?)

-> exchange information about cells traffic load

network issues standardization

- It is need to incorporate more user dedicated information into

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
sa system integration research at comlab hut
SA System Integration Research at ComLab/HUT

- 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)

slide56

Two Users LOS propagation scenario

Center of Helsinki

-75 dB

300

120

60

MS1

-80 dB

160

30

250

-85 dB

250

180

0

200

BS

330

150

210

240

300

270

100

MS2

- incoming impulses from the MS1 - amplitude and AOA

50

- incoming impulses from

the MS2 - amplitude and AOA,

considered as “interference”

for MS1 (and vs)

0

300

250

150

100

200

0

50

basis X-coordinate

- Smart Antenna’s radiation pattern antenna main lobe locked on the signals coming from MS1

Smart Antennas Model

pmr sa new research problems
PMR-SA. New research Problems.

- 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

publications
Publications

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.

12.

(also see at http://www.comlab.hut.fi/thesispub.htm)