Robust beamforming and power allocation in cognitive radio relay networks with imperfect channel state information

The authors study robust beamforming and power allocation in cognitive relay networks using several relays in the secondary link. The channel state information is imperfect modelled by Gaussian random variables. First, minimisation of the total transmit power of relays and the secondary transmitter is considered with a constraint on the interference in the primary receiver. Also, a constraint is assumed on the received signal-to-interference plus noise ratio (SINR) in the secondary receiver. In the other scenario, maximisation of the SINR in the secondary receiver is investigated with a limit on the maximum transmit power of relays and the secondary transmitter. For each non-convex optimisation problem, an iterative and robust algorithm is derived. It is proved that the first proposed algorithm converges to the global optimum. Simulation results similarly show the convergence of both algorithms with a few number of iterations. The outperformance of the robust algorithms is shown compared with a non-robust design.