Considering a heterogeneous network (HetNet) where both macro base station (BS) and small cell (SC) nodes are equipped with massive antennas, this paper studies the performance for multiple-input multiple-output (MIMO) downlinks when the macro and small cells share the same spectrum and hence interfere with each other. Suppose that the large-scale antenna arrays at both macro BS and SC nodes employ maximum-ratio transmission (MRT) or zero-forcing transmission (ZFT) precoding, and transmit data streams to the served users simultaneously. A new pilot reuse pattern among SCs is proposed for channel estimation. Taking into account imperfect channel state information (CSI), capacity lower bounds for MRT and ZFT are derived, respectively, in closed-form expressions involving only statistical CSI. Then asymptotic analyses for massive arrays are presented under specific power scaling laws. Subsequently, two user scheduling algorithms, greedy scheduling algorithm and asymptotical scheduling algorithm (ASA), are proposed based on derived capacity lower bounds and asymptotic analyses, respectively. ASA is demonstrated to be a near optimal in the asymptotic regime and has low complexity. Finally, the derived closed-form expressions are verified to be accurate predictors of the system performance by Monte-Carlo simulations. Numerical results demonstrate the effectiveness of asymptotic analysis and proposed user scheduling schemes.