Adaptive beamforming and energy-efficient routing in wireless networks

In this dissertation, we study some optimal resource utilization problems that arise in wireless communication networks. First, joint transmitter and receiver adaptive beamforming problem is studied, where both transmitters and receivers are equipped with adaptive antenna arrays. The problem is formulated as minimizing the total transmitted power subject to the constraint that the signal quality at all receivers are above a certain threshold or as maximizing the minimum signal-to-interference-and-noise ratio (SINR) of all receivers. We propose iterative algorithms and evaluate the performance via simulation. The results show that the joint transmit and receive beamforming further increases the network capacity or reduces the average transmit power per transmitter compared with the systems having transmit beamforming only or receive beamforming only. We also show by an example that there may exist multiple local optima when the number of directions of interference is not so large compared to the number of antenna array elements. Second, routing in static multihop wireless ad hoc networks is studied. In these networks the top priority is assumed to be the energy efficiency as the communication nodes operate on limited battery energy. This work is based on the notion that the route selection, that is, the choice of the next hop determines the transmit power level if we assume that the optimal transmit power level is used. The objective is to find routing that maximizes the network lifetime. We model and formulate the routing problem as a linear program. A fast approximation algorithm and its distributed implementation as well as some heuristic algorithms are proposed. The results show that shortest cost path routing is very efficient when the link cost is proportional to the energy consumption in the link and inversely proportional to the residual energy levels of the two end nodes of the link. The performance of the proposed algorithms is evaluated through simulation and is shown to be very close to the optimal.