Comparative Analysis of Non-Blind Algorithms on the basis of Sidelobe Level for Smart Antenna System
| dc.contributor.advisor | Murad, Ridwan (PhD) | |
| dc.contributor.author | Seid, Ahmed | |
| dc.date.accessioned | 2020-03-06T06:57:37Z | |
| dc.date.accessioned | 2023-11-28T14:09:11Z | |
| dc.date.available | 2020-03-06T06:57:37Z | |
| dc.date.available | 2023-11-28T14:09:11Z | |
| dc.date.issued | 2018-07 | |
| dc.description.abstract | From time to time the need for good quality communication is required in different aspects of life. Many challenges can face service providers for implementing different communication facilities. One of these great challenges is the limitation of available radio frequency. So it is mandatory to use the scarce resource most efficiently in parallel with providing good quality of service for the customers. One of the way, for efficient utilization of limited radio frequency (RF) spectrum is to use smart antenna system. Smart antenna radiates not only narrow beam towards desired users exploiting signal processing capability but also places null towards interferers, thus optimizing the signal quality and enhancing capacity. The efficiency of the smart antenna can depend on different parameters like angle of separation between the desired and the interferer signal, the number of elements of the array and the spacing between the array elements. Different researches showed that the performance of smart antenna can be improved by using an array with a relatively large number of elements having an optimum spacing between them with a relatively large angle of separation between the desired and the interferer signal. The central aim of this thesis work is comparing the performance of smart antenna in terms of reducing radiation in unintended direction. This is achieved by using an algorithm that produces lower sidelobe level in the radiation pattern of the antenna. Comparative analysis of three nonblind algorithms, Least Mean Square (LMS), Sample Matrix Inversion (SMI) and Recursive Least Square (RLS), on the basis of Sidelobe Level (SLL) is studied in this thesis work. Smart antenna incorporates these algorithms to calculate complex weights according to the signal environment. Simulation results reveal that all the three algorithms have their own beamforming characteristics. But the LMS produces lower sidelobe level as compared to the other two algorithms. Therefore, the LMS algorithm is found the most efficient because of its simplicity, lower complexity and sidelobe level for communication through a flat fading channel. In addition, as the number of elements increases, the sidelobe level of array factor pattern decreases for the case of LMS algorithm. | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/12345678/20923 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Addis Ababa University | en_US |
| dc.subject | Beamforming | en_US |
| dc.subject | LMS | en_US |
| dc.subject | RLS | en_US |
| dc.subject | SMI | en_US |
| dc.subject | Sidelobe Level | en_US |
| dc.subject | smart antenna | en_US |
| dc.title | Comparative Analysis of Non-Blind Algorithms on the basis of Sidelobe Level for Smart Antenna System | en_US |
| dc.type | Thesis | en_US |