  Large-scale antenna (LSA) has gained a lot of attention recently since it can
significantly improve the performance of wireless systems. Similar to
multiple-input multiple-output (MIMO) orthogonal frequency division
multiplexing (OFDM) or MIMO-OFDM, LSA can be also combined with OFDM to deal
with frequency selectivity in wireless channels. However, such combination
suffers from substantially increased complexity proportional to the number of
antennas in LSA systems. For the conventional implementation of LSA-OFDM, the
number of inverse fast Fourier transforms (IFFTs) increases with the antenna
number since each antenna requires an IFFT for OFDM modulation. Furthermore,
zero-forcing (ZF) precoding is required in LSA systems to support more users,
and the required matrix inversion leads to a huge computational burden. In this
paper, we propose a low-complexity recursive convolutional precoding to address
the issues above. The traditional ZF precoding can be implemented through the
recursive convolutional precoding in the time domain so that only one IFFT is
required for each user and the matrix inversion can be also avoided. Simulation
results show that the proposed approach can achieve the same performance as
that of ZF but with much lower complexity.
