Salvatore Bellofiore

Smart-antenna systems for mobile communication networks. Part 1. Overview and antenna design

This paper focuses on the interaction and integration of several critical components of a mobile communication network using smart-antenna systems. This wireless network is composed of communicating nodes that are mobile, and its topology is continuously changing. One of the central motivations for this work comes from the observed dependence of the overall network throughput on the design of the adaptive antenna system and its underlying signal processing algorithms. Part 1 of this two-part paper gives a brief overview of smart-antenna systems, including the different types of smart-antenna systems, and the reason for their having gained popularity. Moreover, details of typical antenna array designs suitable for the wireless communication devices are included in this part.

Smart antenna system analysis, integration and performance for mobile ad-hoc networks (MANETs)

This paper focuses on the interaction and integration of several critical components of a mobile ad-hoc network (MANET) using smart antenna systems. A MANET is a wireless network where the communicating nodes are mobile and the network topology is continuously changing. One of the central motivations for this work comes from the observed dependence of the overall network throughput on the design of the adaptive antenna system and its underlying signal processing algorithms. In fact, a major objective of this work is to study and document the overall efficiency of the network in terms of the antenna pattern and the length of the training sequence used by the beamforming algorithms. This study also considers in sufficient detail problems dealing with the choice of direction of arrival algorithm and the performance of the adaptive beamformer in the presence of antenna coupling effects. Furthermore, the paper presents strategies and algorithms to combat the effects of fading channels on the overall system.

Smart-antenna system for mobile communication networks .Part 2. Beamforming and network throughput

Part 1 of this paper provided an overview of smart-antenna systems, and presented a planar array as a design example. In addition, Part 1 discussed the potential of smart antennas with regard to providing increased capacity in wireless communication networks. Part 2 introduces the signal-processing aspects of the antenna array. In particular, it describes the utility of direction-of-arrival algorithms in array-antenna systems, and gives an overview of the signal-processing algorithms that are used to adapt the antenna radiation pattern. The adaptive-algorithm descriptions are accompanied by simulation results obtained for a specific network topology. In particular, the antenna system is simulated assuming a mobile network topology that is continuously changing. Basic results presented are the dependence of the overall network throughput on the design of the adaptive-antenna system, and on the properties of the adaptive-beamforming algorithms and associated antenna patterns.

Adaptive eigen-projection beamforming algorithms for 1D and 2D antenna arrays

We develop one-dimensional (1D) and two-dimensional (2D) adaptive algorithms that use gradient projections in selected subspaces for use in antenna beamforming. The 1D algorithm is essentially a significantly enhanced version of an eigenspace projection algorithm (EPA) that was previously developed for controls. The 2D algorithm is new and is based on a stacked configuration of the enhanced 1D algorithm. Both algorithms are applied to antenna beamforming in uniform linear and planar arrays. Simulation results show faster convergence as well as improved beam properties. In addition, results for a more realistic scenario, with a BPSK signal and antenna coupling effects, are also quite promising.

Sparse Manifold Learning with Applications to SAR Image Classification

Nonlinear data-driven dimensionality reduction techniques have recently gained popularity due to the emergence of high dimensional data sets. The algorithmic complexity and storage requirements of these techniques, however, can make them prohibitive in resource-limited applications. It is therefore beneficial to reduce the number of exemplar samples required for performing an out-of-sample extension to a test point. In this paper, we propose a novel method for selecting a minimal set of exemplars and performing the out-of-sample extension. In the case of two-class target recognition with synthetic aperture radar (SAR) data, we compare the efficacy of the proposed approach with other approaches for selecting a subset of the available training samples. We show that the proposed algorithm outperforms the existing methods by providing low-dimensional embeddings that maintain interclass separability using fewer retained exemplars.

Smart antennas for wireless communications

Over the last decade, there has been a growing interest in improving system capacity and increasing coverage area in wireless communications using smart antennas. Smart antenna technology is being considered for mobile platforms such as automobiles, cellular telephones (mobile unit), and laptops. This paper presents the design of a smart antenna along with the associated signal processing algorithms for use in the next generation 20 GHz wireless communications systems. The results presented here are part of a broader project that considers this antenna system in the context of reconfigurable broadband (high-speed) networks. This paper concentrates only on the antenna design and on the development of efficient adaptive algorithms for beamforming and direction-of-arrival (DOA). The objective is to design an adaptive antenna that directs the maximum radiation of the antenna pattern toward the signal-of-interest (SOI), and places nulls toward the signal-not-of-interest (SNOI). The proposed antenna design and associated beamforming algorithms take into account mutual coupling for greater accuracy.

Impact of smart antenna designs on network capacity

Smart antenna technology is being considered for mobile platforms such as automobiles, cellular phones (mobile unit), laptops, etc. This paper presents a comprehensive effort on smart antennas that examines and integrates antenna array design, digital signal processing algorithms (for angle of arrival estimation and adaptive beamforming), and the impact of these on the network throughput. The results presented are part of a broader project that considers this antenna system in the context of reconfigurable broadband (high-speed) networks.

Polarization coherency through various scattering mechanisms

A backscattered signal is coherently or incoherently polarized depending on the nature of the scattering surface and the bandwidth of the incident signal. In various applications, and more realistic scenarios, multi spectra or Ultra Wide Band (UWB) have certain advantages over narrow band signals especially in target detection or resolution. Under these circumstances, we investigate the depolarizing effects of wide band signals to understand the relationship of coherency or incoherency with various scattering mechanisms such as reflection/transmission or diffraction. In other words, these major scattering mechanisms may depolarize a signal incoherently in one instance while coherently in another. In this paper we present results showing that the coherency or incoherency of a signal is highly dependent on the nature of the scatterer in relationship to the bandwidth of the incident signal. We use the Finite Difference Time Domain (FDTD) methodology to analyze signals scattering off various homogenous or inhomogeneous surfaces.

Adaptive antenna systems for mobile ad-hoc networks

This paper focuses on the interaction and integration of several critical components of a mobile ad-hoc network (MANET) using smart antenna systems. A MANET is a wireless network where the communicating nodes are mobile and the network topology is continuously changing. One of the central motivations for this work comes from the observed dependence of the overall network throughput on the design of the adaptive antenna system and its underlying signal processing algorithms. In fact, a major objective of this work is to study and document the overall efficiency of the network in terms of the antenna pattern and the length of the training sequence used by the beamforming algorithms. Furthermore, the paper also considers problems dealing with: the choice of direction of arrival algorithm; the performance of the adaptive beamformer in the presence of antenna coupling effects; combating the effects of fading channels on the overall system.