Due to high costs and power consumptions, fully digital baseband precoding schemes are usually prohibitive in millimeter-wave massive MIMO systems. Therefore, hybrid precoding strategies become promising solutions. In this paper, we present a novel real-time yet high-performance precoding strategy. Specifically, the eigenvectors corresponding to the larger eigenvalues of the right unitary matrix after singular value decomposition on an array response matrix are used to abstract the angle information of an analog precoding matrix. As the obtained eigenvectors correspond to the larger singular values, the major phase information of channels is captured. In this way, the iterative search process for obtaining the analog precoding vectors is avoided, and thus the hybrid precoding can be realized in parallel. To further improve its spectral-efficiency, we enlarge the resultant vector set by involving more relevant vectors in terms of their correlation values with the unconstrained optimal precoder, and a hybrid precoder is thus produced by using the vector set. The simulation results show that our proposed scheme achieves near the same performance as the orthogonal matching pursuit does, whereas it costs much fewer complexities than the OMP, and thus can be realized in parallel. INDEX TERMS Millimeter wave communication, MIMO, wireless communication, hybrid precoding. I. INTRODUCTION

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Forming cooperation through relay's assistance is a promising method to realize green communication by reducing transmission power. In this paper, for multiuser single-DF-relay wireless networks with direct links, the optimal power allocation strategy that minimizes system-sum-power consumption is investigated. Based on the principle that minimizing system-sum-power consumption is equivalent to maximizing system energy efficiency, users are classified into two parts after comparing the channel gains between source-destination link and relay-destination link. The optimal power allocation strategy of one part is determined directly, and minimizing the system-sum-power consumption of the other part is converted into minimizing source-sum-power consumption, which can be solved easily through Karush-Kuhn-Tucker (KKT) condition. Through numerical simulations, we further justified the effectiveness of our scheme compared to existing works.

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