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The Machine-To-Machine (M2M) communications allow information exchange between machine devices, which can be carried out without any human interaction. In this paper, the authors propose two iterative strategies to jointly optimize the source antenna selection and the collaborative relay beamforming weights with the aid of perfect Channel State Information (CSI). The aim of the proposed strategies is to maximize the worst-case received Signal-to-Interference-and-Noise Ratio (SINR) under two different types of relay power constraints, which are the total relay power constraint and individual relay power constraints, respectively. Using the Semi-Definite Relaxation (SDR) technique, the optimization problem of collaborative relay beamforming can be formulated as a Semi-Definite Programming (SDP) problem, which can be optimally solved.
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