A New Uplink Channel Estimation Architecture for Massive MIMO Systems with PDMA Massive multiple input multiple output (MIMO) with millimeterwave (mmWave) techniques is favored by nextgeneration communication systems for its higher data rates, and higher spectral energy efficiency. Considering the dualwideband effect existing in the largescale antenna arrays, a new architecture for uplink (UL) channel estimation based on pathdivision multiple access (PDMA) is proposed in this paper. To be specific, we focus our attention on a new method based on successive dichotomy to reduce the searching complexity and achieve better performance than the traditional algorithm, where a selection for quantization is given to save resource overhead. Furthermore, a lowcost VLSI architecture for PDMA, which is easy to implement on hardware, is first proposed.

A Practical Channel Estimation Scheme for SubConnected Hybrid Massive MIMO Systems In massive multipleinput multipleoutput (MIMO) system, the increasing number of antennas causes high power consumption and hardware complexity. Subconnected hybrid system structure can effectively mitigate integration difficulty and reduce the number of radio frequency (RF) chains. Despite losing little degrees of freedom, this structure makes massive MIMO achieved in practice. In this paper, we proposes a uplink channel estimation scheme where a subconnected hybrid massive MIMO base station (BS) communicates with a singleantenna user. Since the sparsity caused by severe path loss, channel state information can be reconstructed by estimating the angles and gains of paths. We apply joint beam selection and sumdifference beam (JBSSDB) method to estimate path angles and utilize least square (LS) method to estimate gains information. Simulation results demonstrate that the proposed scheme achieves lower NMSE than conventional method in the case of same overhead.