Spectrum sharing in wireless networks via QoS-aware secondary multicast beamforming
IEEE Transactions on Signal Processing
On multicast beamforming for minimum outage
IEEE Transactions on Wireless Communications
IEEE Transactions on Signal Processing
Robust adaptive beamforming with null widening under quadratic constraint
AICI'12 Proceedings of the 4th international conference on Artificial Intelligence and Computational Intelligence
Robust Capon beamforming against large DOA mismatch
Signal Processing
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An interesting relationship between the probability-constrained and worst-case optimization based robust minimum variance (MV) beamformers has been discovered. It is shown that both in the cases of circularly symmetric Gaussian and worst-case distributions of the steering vector mismatch, the probability-constrained robust MV beamforming problem can be tightly approximated as a convex second-order cone programming (SOCP) problem. The latter problem is mathematically equivalent to that resulting from the deterministic worst-case approach and, therefore, probability-constrained beamformers can be interpreted and implemented using their deterministic worst-case counterparts. However, an important advantage of the developed probability-constrained MV beamformers with respect to their standard worst-case counterparts is that the former approaches enable to explicitly quantify the parameters of the uncertainty region in terms of the beamformer outage probability.