  The sixth-generation (6G) communication networks target peak data rates
exceeding 1Tbps, necessitating base stations (BS) to support up to 100
simultaneous data streams. However, sparse pilot allocation to accommodate such
streams poses challenges for users' channel estimation. This paper presents
Channel Estimation Considerate Precoding (CECP), where BS precoders prioritize
facilitating channel estimation alongside maximizing transmission rate. To
address the computational complexity of 6G large-scale multi-input multi-output
(MIMO) systems, we propose a computationally-efficient space-time block
diagonal channel shortening (ST-BDCS) precoding scheme. By leveraging the
sparse Toeplitz property of orthogonal frequency division multiplexing (OFDM)
channels, this time-domain precoding design effectively mitigates multi-user
interference in the downlink and shortens the effective channel's temporal
length. Consequently, users can estimate the channels using sparse pilots. To
enable fast implementation, we develop a generalized complex-valued Toeplitz
matrix QR decomposition algorithm applicable to various space-time signal
processing problems. Simulation results demonstrate that the ST-BDCS precoding
method approximates the rate performance of conventional
subcarrier-by-subcarrier precoding schemes. However, it offers the advantages
of easier channel estimation for users and significantly reduced computational
complexity for the BS.
