The proposed worst-case WSR maximization beamformers are obtained via Algorithm 2 with ξ=0.01.
The signal model is presented in Section 2. The proposed worst-case-based distributed beamforming approaches are developed in Section 3. In Section 4, some simulation results are shown to illustrate the performance of the proposed methods, and the conclusions are given in Section 5. Notations Throughout this paper, the bold upper- and lowercase letters denote matrices and vectors, respectively.
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In this paper, we propose two worst-case-based distributed beamforming techniques that are robust to the channel estimation errors.
In this section, we propose two worst-case based distributed beamforming approaches that are robust to the channel estimation errors.
Suppose that imperfect eavesdropper channel condition is considered, we propose a worst-case robust design to obtain distributed jamming weights, which is solved through semi-definite program (SDP).
