Abstract
Taking the channel uncertainty into account, we investigate the robust beamforming design for simultaneous wireless information and power transfer in multiple-input single-output interference channels, where multiple multi-antenna transmitters communicate with their targeted single-antenna receivers and simultaneously interfere with all other receivers. Under quality-of-service and energy harvesting constraints at the receivers which adopt power splitting scheme, we aim to minimize the total transmit power at the transmitters when the channel uncertainty is modeled as the norm-bounded. The robust optimization is non-convex and the global optimal solution is challenging. With the help of the extension of the S-Procedure and rank-one relaxation, the robust beamforming is transformed into a semidefinite programming . We develop an novel method to recover a rank-one feasible and locally optimal solution, which is based on difference of convex programming and sequential parametric convex approximation method. Simulations show that our proposed algorithm outperforms the well-known Gaussian randomization method and has much lower computational complexity.