Some of the material in is restricted to members of the community. By logging in, you may be able to gain additional access to certain collections or items. If you have questions about access or logging in, please use the form on the Contact Page.
Swarm behavior indicates the direct or indirect interactions among relatively simple agents to perform a particular task that is unknown to the individual agent. The study of swarm behavior originates from the research of swarms in nature such as schools of fish or flocks of birds. The attraction of swarm behavior comes from the collective behavior of independent simple agents, each responding to local information without supervision, to perform a global behavior of the entire swarm. The first part of the dissertation investigates the incorporation of swarm behavior in particle filtering to improve the performance of channel estimation in narrow-band multiple-input multiple-output (MIMO) wireless communication systems. Channel estimation is required at the receiver to coherently detect the transmitted symbols and has significant impact on the reliability of the systems. Particle filter is a powerful method to approximate the posterior distribution of the channel information given the received signals in the case of non-linear non-Gaussian systems. However, the particle filter method based on importance sampling has problems of importance density selection and noise uncertainty. The suboptimal particle filters with swarm behavior incorporation in part I are proposed to overcome these problems. On the other hand, part II of the dissertation focuses on class of wireless sensor networks utilizing ultra wide-band (UWB) technology in the physical layer. UWB technology has potential applications in wireless sensor networks with attractive features such as low cost, low complexity, low power, and multiple access efficiency. A network of large number of eventually identical sensor nodes are considered, in which each node has limited resources and capabilities. There are similarities between the sensor node in the network and the agent in a swarm. The second part proposes a self-organizing protocol based on swarm behavior to the UWB wireless sensor networks. The sensor nodes are grouped into clusters, each of which is able to transfer the information toward a data-collecting node along a steep decent path.