This thesis presents a computationally efficient beamforming approach to combat wiretapping in a relay-based multiple-input multiple output (MIMO) communication system which is part of a cognitive radio (CR) network. The system operates in two stages, that is, multiple-access (MA) followed by broadcasting (BC) using physical layer network coding (PNC). The beamforming design is based on minimizing the mean square error (MSE) at the receiving node(s) while enforcing signal-to-interference-plus-noise ratio (SINR) constraints at the eavesdroppers. The constraints take into account uncertainty bounds on eavesdropper channel estimation errors. In each stage of communication, an optimization problem is devised and solved using an iterative procedure, considering two different types of eavesdropper functionality, i.e., selection combining and "blind" beamforming. Numerical results show the convergence of the MSE at the destinations and the SINR distributions at the eavesdroppers for both cases. Results are also compared to those of previously suggested solutions for blind beamforming showing improvements in MSE values in the MA stage as well as in computational efficiency in both stages.
展开▼
