As the growing demand for mobile communications is constantly increasing, the need for better coverage, improved capacity, and higher transmission quality rises. Thus, a more efficient use of the radio spectrum is required. Smart antenna systems are capable of efficiently utilizing the radio spectrum and is a promise for an effective solution to the present wireless systems problems while achieving reliable and robust high-speed high-data-rate transmission. The purpose of this book is to provide the reader a broad view of the system aspects of smart antennas. In fact, smart antenna systems comprise several critical areas such as individual antenna array design, signal processing algorithms, space-time processing, wireless channel modeling and coding, and network performance. In this book we include an overview of smart antenna concepts, introduce some of the areas that impact smart antennas, and examine the influence of interaction and integration of these areas to Mobile Ad-Hoc Networks. In addition, the general principles and major benefits of using space-time processing are introduced, especially employing multiple-input multiple-output (MIMO) techniques.

Introduction to Smart Antennas

In this paper, we investigate spatial multiplexing at millimeter (mm) wave carrier frequencies for short-range indoor applications by quantifying fundamental limits in line-of-sight (LOS) environments and then investigating performance in the presence of multipath and LOS blockage. Our contributions are summarized as follows. For linear arrays with constrained form factor, an asymptotic analysis based on the properties of prolate spheroidal wave functions shows that a sparse array producing a spatially uncorrelated channel matrix effectively provides the maximum number of spatial degrees of freedom in a LOS environment, although substantial beamforming gains can be obtained by using denser arrays. This motivates our proposed mm-wave MIMO architecture, which utilizes arrays of subarrays to provide both directivity and spatial multiplexing gains. System performance is evaluated in a simulated indoor environment using a ray-tracing model that incorporates multipath effects and potential LOS blockage. Eigenmode transmission with waterfilling power allocation serves as a performance benchmark, and is compared to the simpler scheme of beamsteering transmission with MMSE reception and a fixed signal constellation. Our numerical results provide insight into the spatial variations of attainable capacity within a room, and the combinations of beamsteering and spatial multiplexing used in different scenarios.

Indoor Millimeter Wave MIMO: Feasibility and Performance

Owing to the excessive demand on signal processing and space constraint, a full digital implementation of a large adaptive antenna array at millimeter wave frequencies is very challenging. Targeted at long range high data rate point-to-point link in the 70/80 GHz bands, a novel hybrid adaptive antenna array which consists of analogue subarrays followed by a digital beamformer is presented in this paper to overcome the digital implementation difficulty. Two subarray configurations, the interleaved subarray and the side-by-side subarray, are proposed, and two Doppler resilient adaptive angle-of-arrival estimation and beamforming algorithms, the differential beam tracking (DBT) and the differential beam search (DBS), are developed. Simulation results on the DBT and DBS performance are provided using a 64 element hybrid planar array of four 4 by 4 element subarrays with the two subarray configurations, respectively. Recursive mean square error (MSE) bounds of the developed algorithms are also analyzed and compared with simulated MSEs.

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A hybrid adaptive antenna array

This book provides an introduction to narrowband array signal processing, classical and subspace-based direction of arrival (DOA) estimation with an extensive discussion on adaptive direction of arrival algorithms. The book begins with a presentation of the basic theory, equations, and data models of narrowband arrays. It then discusses basic beamforming methods and describes how they relate to DOA estimation. Several of the most common classical and subspace-based direction of arrival methods are discussed. The book concludes with an introduction to subspace tracking and shows how subspace tracking algorithms can be used to form an adaptive DOA estimator. Simulation software and additional bibliography are given at the end of the book.

Narrowband Direction of Arrival Estimation for Antenna Arrays

In this paper, circular and hexagonal array geometries for smart antenna applications are compared. Uniform circular (UCA) and hexagonal arrays (UHA) with 18 half-wave dipole elements are examined; also planar (2 concentric rings of radiators) uniform circular (PUCA) and hexagonal arrays (PUHA) are considered. The effect of rotating the outer ring of the PUCA is studied. In our analysis, the method of moments is used to compute the response of the uniform circular and hexagonal dipole arrays in a mutual coupling environment. The particle swarm optimization (PSO) algorithm is used to optimize the complex excitations, amplitudes and phases, of the adaptive arrays elements for beamforming.

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A Comparison Between Circular and Hexagonal Array Geometries for Smart Antenna Systems Using Particle Swarm Optimization Algorithm

In a beamforming system, mutual coupling among the elements can significantly degrade the system performance. However, the mutual coupling effects can be compensated if an accurate model of mutual coupling is available. This paper utilizes a mutual coupling matrix model to compensate mutual coupling in the beamforming of a uniform circular array. In addition, a circular array of dipoles was built and measurements were performed. The predictions are compared with measurements, and verified with results from full-wave simulations

Mutual Coupling Compensation in UCAs: Simulations and Experiment

In this paper, the minimum-mean-square-error (MMSE) in a mutual coupling (MC) environment is derived. The MMSE is slightly degraded by MC with receiver noise but it is not affected with environmental noise. Analysis also shows that data domain MC compensation cannot improve the minimum MSE even if the estimate of MC is accurate. The simulations also show that MC slows down the convergence of the least mean square algorithm.

The MMSE Algorithm and Mutual Coupling for Adaptive Arrays

In order to provide better field-of-view in elevation and scan the full 3D space, uniform spherical arrays (USA) may be used. This paper presents the analysis of the USA along with an adaptive beamforming algorithm to steer the maximum of the amplitude pattern to the signal-of-interest (SOI) and ideally place nulls to the signals-not-of-interest (SNOI) in 3D space. The ultimate objective is to evaluate the wireless network performance using USA.

Adaptive beamforming using spherical array

It has shown that uniform circular arrays (UCAs) have better performance than uniform rectangular arrays, especially for azimuthal beamforming, when the antenna elements are isolated isotropic point sources. However, in practice, the elements of antenna arrays have physical dimensions and certain radiation characteristics. When two antennas are close to each other, some of the energy from one antenna is coupled to the other, which is referred to as mutual coupling (MC). This paper investigates the beamforming performance of the UCA with real antenna elements and considers the mutual coupling

Mutual Coupling in Beamforming with Circular Array

A system model is presented of adaptive arrays with trellis coded modulation (TCM) to investigate the bit-error-rate (BER) of a wireless system in a co-channel interference environment. Adaptive arrays with different geometries, uniform circular array (UCA), uniform rectangular array (URA) and UCA with center element (UCA-CE), are implemented with the least mean square (LMS) algorithm to combat interference at the same frequency. The wireless systems are investigated in well-separated signals and random direction signals scenarios with additive white Gaussian noise. The URA and UCA-CE have faster convergence and their BERs, in some cases, are slightly influenced by the number of interferers. However, although the UCA converges slowly and its performance degrades as the number of interferers increases, it generally has the best BER. The recursive least square (RLS) algorithm is also investigated. It achieves much better performance than the LMS algorithm when the training sequences are short. However, the optimum BERs attained by these two algorithms are the same.

Zhiyong Huang

Papers

Mutual Coupling Compensation in UCAs: Simulations and Experiment

The MMSE Algorithm and Mutual Coupling for Adaptive Arrays

Adaptive beamforming using spherical array

Mutual Coupling in Beamforming with Circular Array

BER of Adaptive Arrays in AWGN Channel