In this paper, a downlink cooperative channel estimation scheme is proposed for the three-dimensional massive multiple inputs multiple outputs (3D-mMIMO) system operating in the frequency division duplexing (FDD) mode. In the proposed cooperative scheme, users have to cooperate with each other via device-to-device (D2D) communication protocol to jointly exploit the sparsity structure property of the channel. Motivated by the sparsity property of the mMIMO channel in the angle-time domain, a parametric feedback scheme is proposed, where the feedback overhead is decreased by sending a limited version of the estimated coefficients rather than all the coefficients back to the BS. Then, a compressive sensing (CS) algorithm is proposed, which we named weighted fast iterative shrinkage thresholding (WFISTA). In the WFISTA, we first introduce new weights and threshold function to the original FISTA to enhance its sparsity-undersampling trade-off in the single measurement vector (SMV) case, then we extend the proposed WFISTA to the case of multiple measurement vector (MMV) problem by adopting ReMBo (reduce MMV and boost) strategy. The proposed WFISTA has the ability to estimate the mMIMO system's channel coefficients by exploiting the joint sparsity structure through cooperation among users' equipment (UEs). Complexity analysis and the probability of decreasing the feedback overhead are provided for the proposed cooperative estimation scheme. The simulation results verify the efficiency of the proposed cooperative algorithm scheme compared to several joint channel estimations.