SRS-Based CSI Quality Assessment and Selection for MU-MIMO Precoding in 5G NR

Abstract

Stable downlink precoding in time-division duplex (TDD) multi-user multi-input multi-output (MU-MIMO) systems critically depends on the reliability of channel state information (CSI) at the transmitter. In mobile environments, Doppler-induced channel variation, estimation noise, and pilot contamination distort the channel structure, often leading to ill-conditioned matrices and unstable linear precoding. This paper proposes a Doppler-aware CSI reliability framework in which the condition number of sounding reference signal (SRS)-based channel estimates is used as a per-snapshot indicator of spatial robustness. Instead of relying solely on instantaneous CSI, the proposed approach selects the better-conditioned CSI between current and previously estimated channel realizations prior to downlink transmission, thereby improving robustness under mobility. System-level simulations compliant with 5G New Radio specifications are conducted under fixed, increasing, and decreasing Doppler scenarios using clustered delay line (CDL) channel models. Results show consistent gains in throughput and block error rate (BLER), approaching the performance of the perfect channel state information at transmitter (CSIT). Among the considered schemes, regularized zero forcing (RZF) precoding exhibits higher robustness to CSI degradation, while block diagonalization (BD) is more sensitive to Doppler variations. Overall, the proposed method provides a lightweight and standard-compatible solution for improving MU-MIMO precoding reliability in time-varying channels.