Smart Antenna Grid for Outdoor Distributed System
Kivirinta, Rami (2013)
2013
Signaalinkäsittelyn ja tietoliikennetekniikan koulutusohjelma
Tieto- ja sähkötekniikan tiedekunta - Faculty of Computing and Electrical Engineering
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Hyväksymispäivämäärä
2013-09-04
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tty-201309131348
https://urn.fi/URN:NBN:fi:tty-201309131348
Tiivistelmä
The increasing use of smart phones and other connected devices has increased the data capacity demand of wireless networks. The most common networks, the terrestrial cellular networks, have evolved from simple 2nd generation wireless speech-oriented networks to 4th generation high-speed data dedicated networks. Along with this technological evolution the cellular network topology has changed, as well. Cell sizes have become smaller and smaller.
In order to battle the downsides of smaller cells, large amount of equipment and handover overhead, an outdoor distributed antenna system has been introduced as a co-existing alternative to small cells. Previous studies show that capacity and signal level gains are obtained by jointly processing the information from all the antennas.
As a further improvement to the Outdoor Distributed Antenna System the antennas could be replaced with smart antennas which have their own benefits. The smart grid concept was presented and the possible synergy gains were discussed. The possible benefits were beamforming from multiple antennas, angular separation variability per antenna, and the use of single path multiple access and single path single access schemes.
The radio environment was simulated using 3D ray tracing in order to obtain accurate path specific data. The simulation was set in an environment of a simple Manhattan grid with six antennas per cell, and utilised an LTE frequency of 1800 MHz.
The results show that the microcellular environment is a versatile environment with very challenging locations for direction of arrival estimation and single path communication. At worst, the angular separation can be around 0.30° which is very small.
The effect on the signal-to-noise ratio of the traditional beamforming in conjunction with antenna selection strategies is worth studying. Also the novel smart antenna technologies seem implementable in terms of angular separation requirements.
Further investigations are needed especially in the time domain, so that capacity estimations can be made and the estimation error effect in this type of environment can be quantified.
In order to battle the downsides of smaller cells, large amount of equipment and handover overhead, an outdoor distributed antenna system has been introduced as a co-existing alternative to small cells. Previous studies show that capacity and signal level gains are obtained by jointly processing the information from all the antennas.
As a further improvement to the Outdoor Distributed Antenna System the antennas could be replaced with smart antennas which have their own benefits. The smart grid concept was presented and the possible synergy gains were discussed. The possible benefits were beamforming from multiple antennas, angular separation variability per antenna, and the use of single path multiple access and single path single access schemes.
The radio environment was simulated using 3D ray tracing in order to obtain accurate path specific data. The simulation was set in an environment of a simple Manhattan grid with six antennas per cell, and utilised an LTE frequency of 1800 MHz.
The results show that the microcellular environment is a versatile environment with very challenging locations for direction of arrival estimation and single path communication. At worst, the angular separation can be around 0.30° which is very small.
The effect on the signal-to-noise ratio of the traditional beamforming in conjunction with antenna selection strategies is worth studying. Also the novel smart antenna technologies seem implementable in terms of angular separation requirements.
Further investigations are needed especially in the time domain, so that capacity estimations can be made and the estimation error effect in this type of environment can be quantified.