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dc.contributor.authorNabagirinya, Jordana Chantal
dc.date.accessioned2023-09-14T13:15:30Z
dc.date.available2023-09-14T13:15:30Z
dc.date.issued2023
dc.identifier.urihttp://hdl.handle.net/20.500.12281/16398
dc.description.abstractIn modern wireless communication systems, smart antennas equipped with beamforming capabilities play a crucial role in enhancing signal quality, reducing interference, and increasing system capacity. In this project, we focused on the design and simulation of an adaptive beam smart antenna system using MATLAB. The main objective was to develop and implement a beamforming algorithm to enhance the performance of wireless communication systems. The first objective was to design a smart antenna system with multiple antenna elements capable of generating directional findings. By utilizing a combination of antenna elements, the system could focus the beam towards a desired user while simultaneously nullifying interference signals. The second objective involved the development of an adaptive beamforming algorithm. This algorithm was designed to optimize signal phase and amplitude, ensuring precise beamforming capabilities. By adjusting the weights of the signal, the algorithm could effectively form main lobes and minor lobes, further improving the system's performance. The final objective was to evaluate the performance of the smart antenna system. Through extensive simulations and analysis, the system's ability to focus the beam accurately and reject interference was assessed. The algorithm was also evaluated with other beamforming algorithms. The benefits of beamforming were quantified by comparing the performance of the smart antenna system with and without beamforming capabilities. These evaluations provided crucial insights into the effectiveness and efficiency of the adaptive beam smart antenna. As a result of this project, an adaptive smart antenna was successfully designed and implemented. The antenna demonstrated the capability to focus the beam on a desired user while effectively nulling interference signals. The algorithm developed for this purpose allowed for continuous updates to the signal weights, enabling the formation of main lobes and minor lobes. These achievements contribute to the overall improvement of wireless communication systems by enhancing signal quality and reducing interference.en_US
dc.language.isoenen_US
dc.publisherMakerere Universityen_US
dc.subjectWireless communication systemsen_US
dc.subjectSmart antennasen_US
dc.subjectWireless signal qualityen_US
dc.titleDesign and simulation of an adaptive beam smart antenna using MATLABen_US
dc.typeThesisen_US


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