Accurate angle-of-arrival measurement using particle swarm optimization

As one of the major methods for location positioning, angle-of-arrival (AOA) estimation is a significant technology in radar, sonar, radio astronomy, and mobile communications. AOA measurements can be exploited to locate mobile units, enhance communication efficiency and network capacity, and support location-aided routing, dynamic network management, and many location-based services. In this paper, we propose an algorithm for AOA estimation in colored noise fields and harsh application scenarios. By modeling the unknown noise covariance as a linear combination of known weighting matrices, a maximum likelihood (ML) criterion is established, and a particle swarm optimization (PSO) paradigm is designed to optimize the cost function. Simulation results demonstrate that the paired estimator PSO-ML significantly outperforms other popular techniques and produces superior AOA estimates

Tone based MAC protocol for use with Adaptive Array Antennas

This paper presents a novel Tone-based 802.11b protocol for use in wireless networks where nodes are equipped with adaptive array antennas. The protocol relies on the ability of the antenna and Angle of Arrival (AoA) algorithms to identify the direction of transmitters and then beamform appropriately to maximize SINR (Signal to Interference and Noise Ratio) at the receiver. The performance of the protocol is evaluated using detailed simulation in OPNET and Matlab where we demonstrate the benefits of using adaptive antenna arrays. The impact of using different number of antenna elements is also studied for this environment