  Large-scale multiple-input multiple-output (MIMO) communication systems can
bring substantial improvement in spectral efficiency and/or energy efficiency,
due to the excessive degrees-of-freedom and huge array gain. However,
large-scale MIMO is expected to deploy lower-cost radio frequency (RF)
components, which are particularly prone to hardware impairments.
Unfortunately, compensation schemes are not able to remove the impact of
hardware impairments completely, such that a certain amount of residual
impairments always exists. In this paper, we investigate the impact of residual
transmit RF impairments (RTRI) on the spectral and energy efficiency of
training-based point-to-point large-scale MIMO systems, and seek to determine
the optimal training length and number of antennas which maximize the energy
efficiency. We derive deterministic equivalents of the
signal-to-noise-and-interference ratio (SINR) with zero-forcing (ZF) receivers,
as well as the corresponding spectral and energy efficiency, which are shown to
be accurate even for small number of antennas. Through an iterative sequential
optimization, we find that the optimal training length of systems with RTRI can
be smaller compared to ideal hardware systems in the moderate SNR regime, while
larger in the high SNR regime. Moreover, it is observed that RTRI can
significantly decrease the optimal number of transmit and receive antennas.
