Channel Estimation Considerate Precoder Design for Multi-User Massive MIMO-OFDM Systems: The Concept and Fast Algorithms

Abstract

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 system throughput. 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 spectral efficiency performance of conventional subcarrier-by-subcarrier precoding schemes. However, it offers the advantages of accurate effective channel estimation for users and significantly reduced computational complexity for the BS.