Low-Complexity Optimal Estimation of MIMO
ISI Channels with Binary Training Sequences
Shuangquan Wang, Student Member, IEEE, and Ali Abdi, Member, IEEE
In this letter, a novel low-complexity optimal channel estimator using uncorrelated periodic com-
plementary sets of binary sequences is proposed for multiple-input multiple-output (MIMO) intersymbol
interference (ISI) channels. The estimator is optimal since it attains the minimum possible Cram´er-Rao
lower bound (CRLB). Moreover, it can be implemented with very low complexity via ASIC/FPGA,
which makes it suitable and ready for practical MIMO systems.
MIMO, Uncorrelated Complementary Sets, ISI, Channel Estimation, Frequency-Selective Channel.
For quasi-static or slowly-varying fading channels, training-based channel estimation has been widely
used . Some information theoretical guidelines for training sequence design over MIMO intersymbol
channels are given in . However, the sequences given in  may result in high
peak-to-average power ratios (PAPR), which normally should be avoided in practice.
To overcome the above PAPR difficulty, an optimal training-based channel estimator was proposed in
 using uncorrelated aperiodic complementary sets of binary sequences, where the guard period between