Abstract

Abstract It is known that distributed beamforming techniques can improve the performance of relay networks by using channel state information (CSI). In practical applications, there exist unavoidably estimation errors of the CSI, which results in outage of quality of service (QoS) or overconsumption of transmit power. In this paper, we propose two worst-case-based distributed beamforming techniques that are robust to the channel estimation errors. In the worst-case-based approaches, the worst case in a set that includes the actual case is optimized. Therefore, the performance of the actual case can be guaranteed. In our first approach, the maximal total relay transmit power in the set is minimized subject to the QoS constraint. This distributed beamforming problem can be approximately solved using second-order cone programming (SOCP). In our second method, the worst QoS in the set is maximized subject to the constraints of individual relay transmit powers. It is shown that the resultant problem can be approximately formulated as a quasi-convex problem and can be solved by using a bisection search method. Simulation results show that the proposed beamforming techniques are robust to the CSI errors and there is no outage of QoS or power in the proposed methods.

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