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Performance Analysis of Integrating Directional Reception and Realistic Multipath Modelling in Cognitive Communication Systems
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|Title:||Performance Analysis of Integrating Directional Reception and Realistic Multipath Modelling in Cognitive Communication Systems|
|Date Issued:||May 2016|
|Publisher:||[Honolulu] : [University of Hawaii at Manoa], [May 2016]|
|Abstract:||The establishment of a cost effective, reliable, and high data rate wireless communication system in rural areas remains to be a significant challenge that requires a fresh and innovative approach. In this thesis, the development of advanced nodes from a physical layer perspective is proposed with a fully directional antenna array and fast digital signal processing without any modifications in the medium access control layer. The proposed physical layer focused solution is based on the use of broadband directional antennas, integrating accurate propagation modeling resources and adaptive cognitive communication capabilities for real-time applications. It is shown that by integrating these diverse resources in the advanced base station or nodes, it is possible to address and solve the long standing problem of adequate communication and high data rate needs in rural areas.|
Separate hexagonal antenna array is used for user discovery (via scanning) and for data communication with users. Each advanced base station is capable of digital beamforming, beam steering, handover, load management and coordinated multipoint transmission or reception. The directional antennas facilitate base station-to-base station and base station to mobile user connectivity. The predictable time required to estimate the Angle of Arrival (AoA), compute the beamforming weight, and apply the beamforming weights is estimated and inter-frame space where the AoA estimation and beamforming calculation can be applied for IEEE 802.11 is also offered to ensure practical implementation in available standards. Software and hardware simulations confirm that using real devices (FPGAs) it is guaranteed to behave as in the simulation and hence would satisfy the timing constraints.
As a part of effective radio network planning and design, Genetic Algorithm (GA) and geospatial assets are used to place base stations in order to optimize the cellular coverage in rural areas such as Maui Island, Hawaii and Kohala region of the Big Island, Hawaii. Main finding and major results show that instead of four isotropic regular base stations (5 dBi), only two directional antenna array based advanced base stations (19 dBi) can be used to cover approximately the same area for both the islands (~91% for Maui and ~83% for Kohala).
In perspective to this thesis, capabilities for directional antenna systems and related propagation issues to play a more important role in the system level performance of cognitive communication systems are also investigated as part of the environment awareness engine. The proposed adaptive cognitive communication approach is applied at the base station and the performances of two modern communication systems i.e. Orthogonal Frequency Division Multiple Access (OFDMA) and Multiuser Wireless System are evaluated. Investigation is carried out on trade-offs between accuracy in realistic propagation modeling (number of multipath) and computational time as well as determining the most advantageous beamwidth for directional antennas. This approach is designed to help decide not only if employing the channel parameters, and associated processing delays would help in improving the cognitive communications, but also in determining an acceptable level of modeling details that would achieve acceptable cognitive performance in adaptive and real-time processing. Simulations results show that for realistic SNR/bit values, just the path gain and AoA data for as few as 5 paths could be sufficient in forming a propagation model at the receiver while satisfying certain desired performance criteria. When compared to using all the available propagation modeling data, the use of only 5 paths or less results in 85% reduction in computation time required for generating the channel matrix.
|Description:||M.S. University of Hawaii at Manoa 2016.|
Includes bibliographical references.
|Appears in Collections:||
M.S. - Electrical Engineering|
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