## 1 Introduction  
The rapid diffusion of smartphones has triggered extensive diversification in mobile services. Not only is data traffic exploding, but also terminals are crowding public sites such as stations, airports and event venues. Unfortunately, existing frequency resources are depleted, especially in the microwave band, since many kinds of wireless communication systems such as wireless fidelity (Wi-Fi), worldwide interoperability for microwave access (WiMAX) or long-term evolution (LTE) (-Advanced) have turned into voracious consumers. Overcoming this shortfall is a critical issue in wireless communication. Drastic improvements of transmission rate and system capacity are required towards 5 th generation mobile communications (5G) [1]. Promising solutions are to exploit millimeter wave bands for their rich spectrum resources and shrinking the cell size for improved area spectral efficiency [2; 3]. The main problem with using the millimeter wave band is its link budget shortfall. The propagation loss is large and radio frequency (RF) components such as high power amplifiers (HPAs) have limited performance in the millimeter wave band. Application of massive multiple-input multiple-output (MIMO) [4; 5; 6; 7] is one of the most promising palliatives. Massive MIMO can provide large beamforming gain with huge numbers of arrayed antenna elements without high-performance high-cost RF components [8]. Another approach to obtain higher capacity is multiuser MIMO, in which user equipments (UEs) are spatially multiplexed so that they can use the same frequency channel at the same time [9]. Channel environments in the millimeter wave band are considered to be dominated by the Line-of-Sight (LoS) component since the base station (BS) or UEs are required to have highly directive antennas to obtain sufficient transmission/reception gain. In this situation, multiuser diversity gain is expected to increase the system capacity [10] since the inter-user correlation between the UEs is lower than intra-user correlation. In other words, antenna elements in a UE are highly correlated to each other and this causes a large level gap between the 1 st and 2 nd eigenvalues in the LoS dominant single user MIMO channel. Therefore, higher eigenmodes cannot fully contribute to improving the multistream transmission efficiency. Meanwhile, to spatially multiplex several UEs, the BS requires channel state information at the transmitter (CSIT) to suppress inter-user interference (IUI). The accuracy of CSIT is degraded by the channel time variation created by the movement of the UEs or objects around the UEs. Inaccurate CSIT causes incomplete IUI suppression, which degrades the signal-to-interference power ratio (SIR) performance of multiuser MIMO [11]. We have verified one of the massive MIMO benefits, enhanced robustness of multiuser transmission in time-varying-channel environments [12]. Large beamforming gain is, thanks to the excess degrees of freedom (DoF), still higher than IUI leakage after user movement. This contributes to extend the CSI estimation period as well as reducing the feedback overhead [13]. However, critical issues remain with massive MIMO in the millimeter wave band; CSI per antenna between transmitter and receiver is noisy due to the short link budget as mentioned above. Moreover, the computation complexity imposed by eigenmode transmission is excessive due to singular value decomposition (SVD) calculation. This becomes especially serious in wideband systems. To realize 1 st eigenmode reception at a UE with multiple antenna elements, the beam is simply steered toward the BS antenna array. To estimate angle of arrival (AoA) is the straightforward way and multiple signal classification (MUSIC) [14] or estimation of signal parameters via rotational invariant techniques (ESPRIT) [15] are well known legacy algorithms. They were originally developed for signal source analysis, hence auto-correlation matrix calculation with signal outputs via multiple antennas and SVD operation are essential.