Robust Beamforming for Cognitive and Cooperative Wireless Networks

Abstract

In this thesis four different problems in the area of the robust beamforming in cognitive and cooperative wireless networks, namely, robust downlink beamforming in cognitive radio networks, robust joint transceiver optimization in MIMO ad hoc networks, and finally robust relay beamforming for both one-way and twoway relay channels, are studied. In these problems, it is assumed that the channel state information is not perfectly known and its imperfection, is modeled using either a Stochastic Error (SE) model or a Norm Bounded Error (NBE) model. In the case of the SE model of uncertainty, the average performance measure and in the case of the NBE model of uncertainty, the worst case performance measures are optimized. In the former case an algorithm containing second order cone programming problems, and in the latter case, an algorithm containing semidefinite programming problems are proposed to perform the beamforming process. Finally, numerical simulations are provided as well to assess the performance of the proposed algorithms.