Experimental validation of a smart antenna system model

Abstract

IntroductionIn the last decade, the need of effective mobile communication devices has favored the development of wireless technologies. Nowadays, the demand of dealing with complex communication scenarios characterized by multiple users and standards fosters the study of systems able to provide a suitable quality of service (QoS) and an enhanced security [1]. In such a framework, smart antennas have been recognized as promising tools for an efficient management of the physical layer. As a matter of fact, these systems are aimed at maximizing the signal-to-interference-plus-noise ratio (SINR) at the receiver by steering the main lobe of the beam pattern to track the desired signals and placing attenuations to cancel the interferences. With respect to standard solutions, smart antennas allow to increase the channel capacity and the service coverage [2]. Although the effectiveness of a hardware implementation has been theoretically proved, the technological difficulties and costs for the implementation of fullyadaptive solutions prevented up till now the application of smart antennas in wireless communications. Some prototypes have been implemented making use of complex acquisition systems, where the signal is collected at the receiver and at the output of the array elements in order to compute the co-variance matrix [3]. On the other hand, simpler fully-adaptive systems based on the measurement of the received signal at the receiver have been also implemented [4]. In both cases, the effectiveness of the implementation has been assessed by comparing measured and simulated radiation patterns in correspondence with a single interferer incoming from a fixed direction. Recently, a smart antenna prototype characterized by a simple functional scheme has been proposed in [5]. In this implementation, the signals collected by the array elements are suitably weighted by the hardware control unit according to an iterative strategy based on the Particle Swarm Optimizer (PSO) in order to maximize a suitable fitness function. The antenna has been preliminarily validated by considering both the behavior of the SINR in a complex scenario and the capability of placing nulls in suitable positions of the radiation pattern. In addition, the measured quantities have been compared with the simulations provided by a simple system model [6]. In order to take into account the complexity of the hardware implementation, this paper proposes an innovative model of the adaptive system based on the integration of the strategy proposed in [6] with a suitable fitness function. After presenting the mathematical formulation, the proposed approach is validated by considering real data collected in an experiment modeling a complex interference scenario. Mathematical Formulation of the System Modelwhere ( , and a background noise contribution ( )

A Fully-Adaptive Smart Antenna Prototype: Ideal Model and Experimental Validation in Complex Interference Scenarios

“…This paper discusses the implementation of a fully-adaptive smart antenna devoted to the real-time suppression of multiple jammers and focus on the experimental validation by considering complex interference scenarios. The antenna has already been presented by Azaro et al [16,26] and its functionalities have been preliminary assessed by considering a simple experiment [17,27]. The prototype is characterized by a simple functional scheme where the signals collected by the array elements are suitably weighted by the hardware control unit according to an iterative strategy based on a customized version of the Particle Swarm Optimizer (PSO) [18] to maximize a suitable fitness function.…”