| Mobile ad hoc networks have been receiving meteoric attention in recent years due to their fast deployment, and powerful anywhere anytime network access it offers users. One of the limitations in ad hoc networks has been the lack of antenna array integration to improve capacity, spectrum efficiency, power control, and its capability to extend range coverage. These benefits are indisputably an impressive collection of attributes that provide a strong incentive to employ antenna arrays into ad hoc networks to meet the growing demand for expansion. In this research we propose new alternatives for ad hoc network architectures that incorporate antenna arrays. We describe and analyze the digital communication spread spectrum environment together with the effects of propagation in wireless channels, and the related modulation techniques for direct sequence spread spectrum (DSSS) ad hoc networks. We focus on the services and functionality of the PHY and MAC layers, and investigate the hidden node problem with a foreseeable improvement using an antenna array. Detail analysis and design techniques for modeling antenna arrays and spatial diversity are proposed and implemented. The simulation environment is delineated in terms of the network topology, performance metrics, and attributes of the advanced simulator used in this research. The antenna array models designed for this work, were integrated into the simulation scenarios with ad hoc networks, to form an extended grid of experiments for performance evaluation with and without mobility. The captured simulation results were analyzed and quantified to determine improved performance and network impediments in the system. In the final phase we describe the planning that encompassed this research and summarize its scope, the significance of the results obtained from our antenna array models in DSSS ad hoc networks as well as areas needed to be explored in future research. Throughout this work we have made an attempt to provide a thorough analytical background that has guided us through the design of our models, simulation and an in-depth understanding of the results obtained. |
