Multi-hop communications are becoming more and more important due to its flexibility and potential to improve communication coverage and quality. In this paper, we discuss the robust transceiver optimization for multi...Multi-hop communications are becoming more and more important due to its flexibility and potential to improve communication coverage and quality. In this paper, we discuss the robust transceiver optimization for multi-hop amplify-and-forward multiple-input multiple-output(MIMO) orthogonal frequency division multiplexing(OFDM) systems. In general, we consider a three-dimensional robust beamforming design, i.e.,frequency, spatial and relay domains. With inevitable channel estimation errors, in our work both weighted mean square error(MSE) minimization and minimizing maximum MSE are adopted as the performance metrics to design robust transceivers. Following the Bayesian robust philosophy, a robust transceiver design is proposed. The design is based on convex optimization, and the involved optimization variables are optimized alternatively. The proposed transceiver optimization algorithms can be applied to the network with arbitrary hops, arbitrary antennas and arbitrary subcarriers. At the end of this paper, the performance advantages of the propose design have been assessed by the numerical results.展开更多
基金partly supported by the Fundamental Research Funds for the Central Universities(No.2015QNA4046)
文摘Multi-hop communications are becoming more and more important due to its flexibility and potential to improve communication coverage and quality. In this paper, we discuss the robust transceiver optimization for multi-hop amplify-and-forward multiple-input multiple-output(MIMO) orthogonal frequency division multiplexing(OFDM) systems. In general, we consider a three-dimensional robust beamforming design, i.e.,frequency, spatial and relay domains. With inevitable channel estimation errors, in our work both weighted mean square error(MSE) minimization and minimizing maximum MSE are adopted as the performance metrics to design robust transceivers. Following the Bayesian robust philosophy, a robust transceiver design is proposed. The design is based on convex optimization, and the involved optimization variables are optimized alternatively. The proposed transceiver optimization algorithms can be applied to the network with arbitrary hops, arbitrary antennas and arbitrary subcarriers. At the end of this paper, the performance advantages of the propose design have been assessed by the numerical results.
