Adaptive Beamforming With Joint Robustness Against Mismatched Signal Steering Vector and Interference Nonstationarity

Abstract

Adaptive beamforming methods degrade in the presence of both signal steering vector errors and interference nonstationarity. We develop a new approach to adaptive beamforming that is jointly robust against these two phenomena. Our beamformer is based on the optimization of the worst case performance. A computationally efficient convex optimization-based algorithm is proposed to compute the beamformer weights. Computer simulations demonstrate that our beamformer has an improved robustness as compared to other popular robust beamforming algorithms.Index Terms-Adaptive beamforming, interference nonstationarity, robustness, second-order cone programming, steering vector errors.

Robust receive beamforming with interference and channel uncertainty

“…We can see that the modified channel probability constraint (14) is tighter than the one proposed in [11], but both fulfill the probability constraint (9). Figure 2 shows a typical CDF for the data power w H Rw, whose value should be less than η with probability p = 0.9 according to (10). We can see that the probability constraint (10) is as fulfilled.…”

“…Designs for deterministic uncertainty regions have been studies extensively [5]- [7], [9], [10], including algorithms that consider both channel distortion and interference covariance uncertainty [5]. However, under stochastic uncertainty model, existing algorithms are only robust against channel distortions [11] while neglecting the role of interference covariance matrix estimation errors.…”

Beam forming and modelling in cognitive radio wireless networks

“…In case the information of optimal signal vector is concomitant with error in conventional techniques, the performance is significantly decreased [4] and [9][10][11]. This performance directs the design toward optimization in the worst situation [12][13][14][15][16][17][18][19]. The distribution pattern formers vector is obtained while assuming that the limitations output possibility is lower than what has been determined.Convex optimization is used for solving the problems in these methods.…”

The Sign-Definiteness Lemma and Its Applications to Robust Transceiver Optimization for Multiuser MIMO Systems

“…Later contributions to the topic include [5]- [7], [9], [11]- [13]. Next we will review the March 7, 2013 DRAFT most recent works which are related to our applications.…”

“…Further fundamental contributions on robust beamforming can be found in, e.g., [5]- [13] (see also the references therein).…”