| With recent advances in wireless communications and electronics, the development of low-cost, low-power wireless sensor nodes becomes feasible. Many useful applications are emerging such as military surveillance, target tracking or environmental monitoring. These sensor nodes are usually operated by batteries with limited energy. Therefore power efficiency is the primal concern in almost every application. Two ways of achieving power efficiency are distributed and cooperative processing. In distributed processing, each node does its own local processing and communicates only with its nearby nodes.; In cooperative processing, nodes can reduce the amount of energy required for certain operations by the help of its neighboring nodes.; In this dissertation, we first present distributed algorithm for node localization. Each node estimates its own location and exchanges information with its neighboring nodes. We also show the convergence property of the distributed algorithm.; Next, energy-aware cooperative transmission strategies are considered in which a small number of nodes cooperatively transmit information to a destination node. Based on the residual energy levels of these nodes, we try to maximize the lifetime of the network, while maintaining a certain quality of service (QoS) at the destination node. We show that the lifetime-maximizing strategies significantly outperform the traditional minimum total energy approaches in terms of the network lifetime.; Finally, we investigate the performance of a binary communication system in terms of bit error rate, where the interference is non-exactly known. Methods for computing tighter error probability bounds using semidefinite programming (SDP) are presented. |
