Smart Antennas is perhaps the most promising techniques available in the radio network.
Interest in this technology is increasing today since spatial processing is considered as
a "last frontier" in evolution of multiple access systems. There are not so many
techniques currently proposed for cellular radio network design, which are able to improve
system performance dramatically and smart antennas technique is among them. SA can be
effectively combined with other techniques such as multi-user detection, polarization
diversity, channels coding. Air interfaces standards become more "friendly" for
SA and future introduction of software radio will make possible to make radio system
design optimized for spatial processing and integrate SA into future adaptive modems.
There are number SA commercial products available on the market today.
The main advantages expected with SA are:
- Higher sensitive reception
- Possibility to implement systems with spatial division multiple access (SDMA)
- Interference cancellation in uplink and downlink
- Mitigation effects of multipath fading
- Possibility of very high bit rate data transmission (real time video) in systems with
multilple input - multiple output (MIMO) [10]
On the system level this leads to the higher capacity, extended range, improved coverage
by "in-filling" dead spots, higher quality of services, lower power consumption
at the mobile and improved power control.
SA increases system complexity and costs, but at the same time provides additional degree
of freedom for the radio network control and planning.
During last decade a lot of attention in SA research was paid to different combinations of
SA optimization methods and criteria, channel estimation techniques and receiver
structures. One of the main problems in this area - SA system integration into existing
and future cellular networks was not highlighted yet. SA receiver structure and
algorithms, network control and planning are the main cellular system components to be
considered when SA technology will be introduced. To improve radio network performance
with SA receiver structure and algorithms should be optimized according to the propagation
and interference environment, considering expected traffic and users mobility in the cell.
These parameters can be seen as a product of radio network planing. At the same time, SA
receiver parameters are important for capacity, coverage and interference planning, they
are also tightly interacting with network control protocols at different layers.
Only integrated and multidisciplinary approach for this large topic is able to provide
economically and technically reasonable solutions. It includes (jointly) determining of
relevant SA algorithms and receiver structures, development of new network control
algorithms/protocols which should be aware of spatial properties of signals, upgrade of
simulation/planning tools and revision of network planning methods.
Proposed plan is the extension of the activity started in RAVE project and supposed to
be focused on the network with SA control algorithms development and studies. In RAVE it
was studied
impact of non-uniform traffic distribution on system performance of CDMA radio network
[1],
feasibility of SA receiver with propagation environment and offered traffic, air interface
feasibility, network control and planning with SA [2,3,6,7]. Simulation tool
"NetSim" was further upgraded to introduce SA at the up and down links [4,5].
Co-operation with other groups in RAVE project was established.
2.1. Accomplished tasks
The following tasks were accomplished and results were reported in publications during the reporting period:
2.1.1. Network simulation tools "NetSim" up-grade with smart antennas
Network simulation tool NetSim initially developed at Communication Laboratory several
years ago was further upgraded to include smart antennas module. Developed model can
simulate different types of smart antenna algorithms such as conventional beamformer,
algorithms that include optimization procedure and combination of both these methods. SA
model was developed for up and down -links. SA can be simulated during initial login into
network and data transmission phases.
Several changes in "NetSim" were done to upgrade it to UTRA air interface (users
models with multi-rate services)
Created propagation data files for larger electronic map area of downtown of Helsinki with
larger amount of BS. Improved propagation data processing module and visualization tool to
provide spatial reference for propagation data and simulation results.
Improvement of main CDMA radio network system parameters with developed models
were studied by simulations. Results of impact of SA on network coverage, capacity,
qualities of services for different types of service mix were obtained. Upgraded
simulation tool can be further used for development of network planning methods and
control algorithms development with SA.
Results of this framework were reported in reference [2,3].
Co-operation with other groups:
Other laboratories widely used provided propagation data in their research (Radio Lab.,
Lab of Telecom Technology)
Co-operation with control laboratory was established on "NetSim" up-grade. Input
for "Netsim" upgrade was provided.
2.1.2. Study of impact of non-uniform traffic distribution on system performance of CDMA radio network
Non-uniform traffic spatial distribution is the very likely event in any type of radio
network.
It was done analytical and simulation study of CDMA network system performance with
non-uniform traffic. Derived compact analytical expressions that describe CDMA system
coverage and capacity for different types of non-uniform pattern of traffic distribution.
Non- uniform spatial distribution model was developed for "NetSim" to verify
derived analytical expressions by simulations.
Obtained results can be useful for the initial phase of CDMA network planning process.
More detailed information can be found in the reference [1].
SA is able to play an important role in smoothing traffic load variations due to extended
coverage and dynamic range. In order to be able to exploit these advantages a proper
network control protocols/algorithms should be introduced (joint optimum beamforming, BS
assignment and power control).
2.1.3. Study of feasibility of SA receiver with propagation environment and offered traffic. Air interface feasibility with SA. Network control and planning with SA.
There are a large number of SA types and algorithms being proposed during last two
decades. They vary not only in their performance but what is the most important they can
be applicable only in some certain types of propagation and interference environments.
Different types of SA can be feasible only with certain types of air interfaces.
A classification of different types of SA receivers/transmitters structures and algorithms
was made. Feasibility of different types of SA algorithms with propagation environment,
expected level of interference and mobility rate had been studied. Compatibility of SA
with different types of air interfaces was evaluated.
Several new additional features in standards, which may be required to achieve more
considerable improvements in system performance, were proposed. It was shown that the most
dramatic improvements in system performance could be achieved with proper combination of
different SA algorithms instead of implementation very sophisticated and complex SA
algorithms. Impact of SA on different phases of radio network planning was evaluated.
Network control with SA is another important issue that should be considered. Required
link level protocol modifications and resource management was discussed. The more
improvement we expect to obtain with SA the more resource management should be aware about
spatial properties of signals.
Results of this framework are reported in references [4,5] and several invited
lectures/workshops [6,8]. Bringing together this information had been first time reported
in the literature and had attracted considerable interest. This work will be continued
taking into consideration overview of mathematical models, SA transmitter algorithms, MIMO
systems, and latest achievements in network control and will result in journal paper.
2.1.4. Study of joint optimal beamforming, BS assignment and power control algorithm
Joint optimal power control and beamforming (or combing) algorithms can improve cells
capacity
of traditional networks (GSM) and data rate in systems with elements of link adaptation
(EDGE). Further capacity improvement and smooth of load variation between cell will be
achieved, if BS assignment algorithm will be included in the optimization procedure. Joint
power control and beamforming algorithms can be efficiently applied into the systems with
MIMO.
Developed and analytically evaluated joint algorithm for MIMO system based on MSE
approach. Results will be reported in conference paper. Algorithm will be further extended
with MLSE approach and performance will be evaluated. Algorithms will be a part of system
proposal with will include MIMO combined with downlink beamforming and adaptive resource
management.
During this period it is supposed to obtain more explicit understanding of MIMO system
control design. Algorithms that include joint adaptive spatial processing, temporal
processing and coding will be studied in order to find relevant trade-offs between system
parameters for different propagation and interference environments, users mobility
scenarios. Interfaces like EDGE and UTRA will be considered with main focus on the
down-link transmission. Joint optimal up-link and down link spatial-temporal processing
algorithms will be considered. Proposed algorithms will be able to improve soft-capacity
of the MIMO systems.
Jointly optimal power control and beamforming algorithms can improve cell capacity
and data rates in systems. Achievable improvements with SA can be even more considerable
in systems with elements of link adaptation. If in the optimization procedure also
includes a BS assignment algorithm system capacity can be further improved. Special
attention in this research will be focused on the joint algorithms based on the MLSE
approach. Feasibility of downlink beamforming and MIMO receiver will be studied for this
approach.
Developed analytical model can be further used in the MIMO system design, network control
algorithms/protocols development and network planning. Network simulation tool
"NetSim" will
be further updated with MIMO model.
3.1. Sub -tasks for year 2000
- Jointly optimal receiver-transmitter MIMO spatial-temporal processing and power
control algorithm development.
- Study achievable capacity improvements with developed algorithms
- Simulation tool development. "NetSim" upgrade with MIMO model
- MLSE approach study. Spatial-Temporal coding issues studies which can be applicable for
layered MIMO system architecture
- Dynamic behavior of developed algorithms study by simulation
3.2. Sub -tasks for year 2001 (preliminary)
- Study feasibility of link adaptation algorithms with joint PC, beamforming in MIMO
systems
- System performance and dynamic behavior studies.
- Feasibility with EDGE and UTRA air interfaces. Tuning MIMO - EDGE /UTRA system
parameters for different environments
Acronyms:
MIMO - multiple input multiple output
MLSE - Maximum Likelihood Sequence Estimation
[1] Boukalov Adrian, Sven-Gustav Häggman and Antti Pietilä "Study the Impact of Non-uniform Spatial Traffic Distribution on the System Parameters of CDMA Cellular Network " Proceedings of IEEE International Conference on Personal Wireless Communications (ICPWC'99), February 17 -19, 1999, Jaipur, India, pp. 394 - 398.
[2] 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
[3] Boukalov Adrian, Sven-Gustav Häggman " UMTS Radio Network Simulation with Smart Antennas" to be published in book Wireless Personal Communications, Kluwer Academic Publishers, 2000.
[4] 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. Is this the publications [4]?
[5] 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. / Power Point presentation.
[6] Boukalov Adrian, "Introduction to Smart Antennas Techniques and Algorithms" Workshop on Smart Antennas Technology and Applications at RAWCON 99, 1st August 1999. / Power Point presentation.
[7] Boukalov Adrian , Sven-Gustav Häggman " System Aspects of Smart Antennas Technology in Wireless Communications" accepted paper for IEEE Transaction in Microwave Theory and Techniques will be published in 2000
[8] 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.
[9] Boukalov Adrian "Smart Antennas in Cellular CDMA- Systems" , Presentation in Merito Forum's seminar on advanced radio network design. / Power Point presentation.
[10] 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.
Presentation on Radio Network Simulator "Netsim"
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 technology 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. *
* - publication not available in electronic form