The use of millimeter-wave (mmWave) and full-dimensional multiple-input multiple-output (FD-MIMO) antenna systems for 3D wireless communication is being exploited for enhanced network capacity improvement in the ongoing fifth-generation (5G) deployment. For adequate assessment of competing air interface, random access channelization, and beam alignment procedure in mmWave systems, adequate channel estimation and channel models for different use scenarios are necessary. Conventional pilot-based channel estimation methods are remarkably time-consuming as the number of users or antennas tends toward large numbers. Channel reconstruction has been identified as one of the solutions to the above problem. In this work, a ray-tracing study was conducted using a Wireless Insite ray tracing engine to predict measured statistics for large-scale channel parameters (LSPs). Other LSP such as the shadow fading (SF) were generated using algorithm 1. Algorithm 2 was used to generate the small-scale channel parameters (SSP). The LSPs and SSPs were used as input in algorithm 3 to generate the channel coefficients used for the channel reconstruction in the MATLAB LTE toolbox. The results provided an accurate reconstructed downlink channel state information (CSI) for FDD-based mmWave massive-MIMO system in both the line-of sight (LOS) and non-line of sight scenarios. The results provide an opportunity to adapt the transmitted signal to the CSI and thereby optimize the received signal for spatial multiplexing or to achieve low bit error rates in wireless communication.