Abstract
This paper presents a tool for the analysis, and simulation of direction-of-arrival estimation in wireless mobile communication systems over the Rayleigh fading channel. It reviews three subspace based methods of Direction of arrival estimation algorithms. The standard Multiple Signal Classification (MUSIC) can be obtained from the subspace based methods. In improved MUSIC procedure called Cyclic MUSIC, it can automatically classify the signals as desired and undesired based on the known spectral correlation property and estimate only the desired signal’s DOA. The next method is an extension of the Cyclic MUSIC algorithm called Extended Cyclic MUSIC by using an extended array data vector. By exploiting cyclostationarity, the signal’s DOA estimation can be significantly improved. In this paper, the DOA estimation algorithm using the de-noising pre-processing based on time-frequency conversion analysis is proposed, and the performances are analyzed. This is focused on the improvement of DOA estimation at a lower SNR and interference environment. This paper provides a fairly complete image of the performance and statistical efficiency of each of above three methods with QPSK signal model for coherent system.
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