The rapid growth in wireless data traffic in recent years has placed a great strain on the wireless spectrum and the capacity of current wireless networks. In addition, the makeup of the typical wireless propagation environment is rapidly changing as a greater percentage of data traffic moves indoors, where the coverage of radio signals is poor. This dual fronted assault on coverage and capacity has meant that the tradition cellular model is no longer sustainable, as the gains from constructing new macrocells falls short of the increasing cost. The key emerging concept that can solve the aforementioned challenges is smaller base stations such as micro-, pico- and femto-cells collectively known as small cells. However with this solution come new challenges: while small cells are efficient at improving the indoor coverage and capacity; they compound the lack of spectrum even more and cause high levels of interference. Current channel models are not suited to characterise this interference as the small cells propagation environment is vast different. The result is that overall efficiency of the networks suffers. This thesis presents an investigation into the characteristics of the wireless propagation channel in small cell environments, including measurement, analysis, modelling, validation and extraction of channel data. Two comprehensive data collection campaigns were carried out, one of them employed a RUSK channel sounder and featured dual-polarised MIMO antennas. From the first dataset an empirical path loss model, adapted to typical indoor and outdoor scenarios found in small cell environments, was constructed using regression analysis and was validated using the second dataset. The model shows good accuracy for small cell environments and can be implemented in system level simulations quickly without much requirements.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:678864 |
| Date | January 2015 |
| Creators | Fang, Cheng |
| Publisher | University of Bedfordshire |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/10547/595693 |
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