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This work analyses the performance-complexity tradeoff for different direction of arrival (DoA) estimation techniques. Such tradeoff is investigated taking into account uniform linear array structures. Several DoA estimation techniques have been compared, namely the conventional Delay-and-Sum (DS), Minimum Variance Distortionless Response (MVDR), Multiple Signal Classifier (MUSIC) subspace, Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), Unitary-ESPRIT and Fourier Transform method (FT-DoA). The analytical formulation of each estimation technique as well the comparative numerical results are discussed focused on the estimation accuracy versus complexity tradeoff. The present study reveals the behavior of seven techniques, demonstrating promising ones for current and future location applications involving DoA estimation, especially for 5G massive MIMO systems. 2 an electromagnetic wave into a voltage. The electromagnetic waves are necessary for wireless communications systems implementation. Array signal processing applications include radar and wireless communication systems with electromagnetic waves and sonar, seismic event prediction, microphone sensors with mechanical waves [1]-[3]. In a typical application, an incoming wave is detected by an array, the associated signals at different sensors in space can be processed to extract various types of information including their direction of arrival (DoA). The array model is illustrated in Fig. 1. Moreover, the spatial-temporal estimation and filtering capability can be exploited for multiplexing co-channel users and rejecting harmful co-channel interference that may occur because of jamming or multipath effects. DoA algorithms can be divided into three categories: extrema-searching techniques [4]-[10], polynomial-rooting techniques [11] and matrix-shift techniques [12], [13]. The matrix-shift techniques utilize estimates of the signal subspace whereas most extrema-searching techniques and most polynomial-rooting techniques use estimates of its orthogonal complement, often referred to as noise subspace.The DoA estimation process has been extensively researched since the 1980s, but the research area remains active, mainly due to recent and newly field of applications [14], [15]. Recent studies are mostly focused on specific applications and new approaches to the subject in order to improve performance while decrease computational complexity as well. For some DoA applications it is necessary to estimate the location of sources near and far from the array. For instance, in [16] and [17] DoA techniques are discussed for far-field and near-field sources. To achieve greater accuracy in DoA, a large number of antennas are required, and this is not always feasible, either by physical space or cost limitations.

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