As an emerging paradigm, supplying power by radio frequency signal has been a key technology for the wireless powered communication network (WPCN) to prolong the lifetime. This paper considers a multiple input multiple output (MIMO) system where users are charged only by one source. The source is equipped with multiple antennas while each user with one antenna. Besides receiving information as the traditional way, the source has the capacity to transfer energy with beamforming, which can be

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... ested by users to store for information transmission in the later. However, the unknown channel state information (CSI), low energy efficiency, and various demands of transmitting volume jointly raise inaccurate, wasteful, and flexible conditions in transmitting design. On the other hand, energy and spectrum efficient solutions are indispensable to the success of Internet of Things (IoT). In this case, we put forward a novel design of downlink energy transfer, uplink information transmission, and channel estimation to achieve a practical efficient transmission. By jointly optimizing the source antenna number, power allocation, energy beamforming vectors, and each phase time of channel estimation, energy harvest, and information transmission, we aim to achieve the optimized system energy efficiency with constraints of signal-to-noise ratio (SNR), data transmission volume, and transmitting power. Based on fractional programming and Lagrangian dual functions, we also put forward a distributed iterative algorithm to solve the formulated problem optimally. Simulation results verify the convergence of our proposed algorithm and illustrate the relationship between variables of antenna number, data volume requirement, pathloss factor and system performance of sum-throughput, energy efficiency, and user fairness. Our proposed transmitting design can achieve the optimized energy efficiency, whose upper bound is improved by appropriate massive antenna employment.