A multibeam massive multiple input multiple output (MIMO) configuration employs beam selection with high power in the analog part and executes a blind algorithm such as the independent component analysis (ICA), which does not require channel state information in the digital part. Two-dimensional (2-D) multibeams are considered in actual power losses and beam steering errors regarding the multibeam patterns. However, the performance of these 2-D beams depends on the beam pattern of the multibeams, and they are not optimal multibeam patterns suitable for multibeam massive MIMO configurations. In this study, we clarify the performance difference due to the difference of the multibeam pattern and consider the multibeam pattern suitable for the system condition. Specifically, the optimal multibeam pattern was determined with the element spacing and beamwidth of the element directivity as parameters, and the effectiveness of the proposed method was verified via computer simulations.

This paper investigates energy-efficient resource allocation problem for the wireless power transfer (WPT) enabled multi-user massive multiple-input multiple-output (MIMO) systems. In the considered systems, the sensor nodes (SNs) are firstly powered by WPT from the power beacon (PB) with a large scale of antennas. Then, the SNs use the harvested energy to transmit the data to the base station (BS) with multiple antennas. The problem of optimizing the energy efficiency objective is formulated with the consideration of maximum transmission power of the PB and the quality of service (QoS) of the SNs. By adopting fractional programming, the energy-efficient optimization problem is firstly converted into a subtractive form. Then, a joint power and time allocation algorithm based on the block coordinate descent and Dinkelbach method is proposed to maximize energy efficiency. Finally, simulation results show the proposed algorithm achieves a good compromise between the spectrum efficiency and total power consumption.