DEVELOPMENT AND ANALYSIS OF ADAPTIVE BEAMFORMING SCHEME FOR A SMART ANTENNA SYSTEM USING THE NORMALIZED LMS TECHNIQUE

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dc.contributor.author AZEBAZE, JOSEPH PAULIN NAFACK
dc.date.accessioned 2018-06-27T11:19:23Z
dc.date.available 2018-06-27T11:19:23Z
dc.date.issued 2018-06-27
dc.identifier.citation AZEBAZE2018 en_US
dc.identifier.uri http://hdl.handle.net/123456789/4696
dc.description degree of Master of Science in Electrical Engineering (Telecommunication Engineering Option) en_US
dc.description.abstract Adaptive beamforming using smart antennas is one of the potential solution to the demand for increased capacity in wireless communication networks. The Least Mean Square (LMS) algorithm has been identified as a suitable technique that optimises the Signal to Noise Ratio (SNR) of the desired signal in a particular direction. However, although it gives an optimum solution, the LMS exhibits slow convergence rate. This thesis proposes the development and the analysis of the Normalized Least Mean Square (NLMS) algorithm as a method to improve the convergence rate of the standard LMS algorithm thus, increasing channel capacity and spectrum efficiency. The proposed adaptive beamforming scheme uses an array of antennas to realise maximum reception in a specified direction. This is achieved by adjusting the weights of each of the antennas with changing signal environment. The NLMS algorithm is an extension of LMS algorithm where the step size parameter is chosen based on current input values. It shows greater stability with unknown signals. The theoretical formulation results show an insignificant increase in the computational complexity of the NLMS algorithm. The simulation results for both the NLMS and the standard LMS agree closely. However, it is established that the proposed method has a better convergence rate of the Mean Square Error (MSE) and updates the weights in less number of iterations in time precisely 12 iterations. The performance of the NLMS algorithm is compared to that of the block LMS algorithm and Recursive Least Squares. The proposed algorithm performed better in terms of beam steering (narrower beam at the desired angle 30°), and in terms of null deep capability-42dB as compared to the block LMS algorithm -30dB and the RLS algorithm -41.94dB. en_US
dc.description.sponsorship Prof. Elijah Mwangi University of Nairobi, Kenya Prof. Dominic B. O. Konditi Technical University of Kenya en_US
dc.language.iso en en_US
dc.publisher JKUAT en_US
dc.subject ANALYSIS OF ADAPTIVE en_US
dc.subject DEVELOPMENT en_US
dc.subject BEAMFORMING SCHEME en_US
dc.subject SMART ANTENNA SYSTEM en_US
dc.title DEVELOPMENT AND ANALYSIS OF ADAPTIVE BEAMFORMING SCHEME FOR A SMART ANTENNA SYSTEM USING THE NORMALIZED LMS TECHNIQUE en_US
dc.type Thesis en_US


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