Application of DOA Estimation Algorithms in Smart Antennas Systems

Tanuja S. Dhope (Shendkar)
Faculty of Electrical Engineering and Computing, University of Zagreb
Croatia
Dina Simunic
Faculty of Electrical Engineering and Computing, University of Zagreb
Croatia
Marijan Djurek
Faculty of Electrical Engineering and Computing, University of Zagreb
Croatia

Abstract: Concept of wireless communication systems which use smart antennas is based on digital signal processing algorithms. Thus, the smart antennas systems become capable to locate and track signals by both: users and interferers and dynamically adapts the antenna pattern to enhance the reception in Signal-Of-Interest direction and minimizing interference in Signal-Of-Not-Interest direction. Hence, Space Division Multiple Access system, which uses smart antennas, is being used more often in wireless communications, because it shows improvement in channel capacity and co-channel interference. However, performance of smart antenna system greatly depends on efficiency of digital signal processing algorithms. The algorithm uses the Direction of Arrival (DOA) algorithms to estimate the number of incidents plane waves on the antenna array and their angle of incidence. This paper investigates performance of the DOA algorithms such as MUSIC, ESPRIT and ROOT MUSIC on the uniform linear array in the presence of white noise. The simulation results show that MUSIC algorithm is the best. The resolution of the DOA techniques improves as number of snapshots, number of array elements and signal-to-noise ratio increases.

Keywords: smart antenna, DOA, MUSIC, ESPRIT, ROOTMUSIC, SDMA, adaptive beamforming.

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CITE THIS PAPER AS:
Tanuja S. Dhope (Shendkar), Dina Simunic, Marijan Djurek, Application of DOA Estimation Algorithms in Smart Antennas Systems, Studies in Informatics and Control, ISSN 1220-1766, vol. 19 (4), pp. 445-452, 2010.

1. Introduction

The high demand on the usage of the wireless communication system calls for higher system capacities. The system capacity can be improved either by enlarging its frequency bandwidth or allocating new portion of frequency spectrum to wireless services. But since the electromagnetic spectrum is a limited resource, it is not easy to get new spectrum allocation without the international coordination on the global level. One of the approaches is to use existing spectrum more efficiently, which is a challenging task. Efficient source and channel coding as well as reduction in transmission power or transmission bandwidth or both are possible solutions to the challenging issue. With the advances in digital techniques, the frequency efficiency can be improved by multiple access technique (MAT), which gives mobile users access to scarce resource (base station) and hence improves the system's capacity [1]. Family of existing Frequency Division Multiple Access (FDMA), Time Division Multiple Access (TDMA) and Code Division Multiple Access (CDMA) can be enlarged by adding a new parameter 'space' or 'angle' [2], which results in MAT known as 'Space Division Multiple Access' (SDMA). At the receiver's side, the transmitted signal is received with its multipath components plus interferers' signal, as well as with present noise. Thus, detection of the desired signal is a challenging task. The Smart Antenna System (SAS) employs the antenna elements and the digital signal processing which enables it to form a beam to a desired direction taking into account the multipath signal components. In this way, Signal-to-Interference-and-Noise Ratio (SINR) improves by producing nulls towards the interferers in the direction of Signal-Of-Not-Interest (SONI) [3].The performance of SAS greatly depends on the performance on DOA estimation.

The subspace based DOA estimation algorithms MUSIC, ESPRIT and ROOTMUSIC provide high resolution, are more accurate and are not limited to physical size of array aperture [2][5]. In this paper we are investigating the performance of MUSIC, ESPRIT and ROOT MUSIC algorithms. The performance of these algorithms is analysed by considering parameters like number of array elements, user space distribution, number of snapshots, signal to noise ratio, Mean Square Error (MSE), which results in optimum array design in SAS.

The conclusions of the work are drawn from the simulated results using MATLAB.

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