Performance Evaluation of Channel Estimation Methods for 5G NR Uplink Control Channel in the Scenario of Low Signal-to-Noise Ratios

This study evaluated the performance of various channel estimation techniques for the physical uplink control channel, which plays a crucial role in the state-of-the-art telecommunication 5G NR technology. We considered the conventional least-square (LS), DFT-based LS, moving-average LS, and minimum-mean-square-error (MMSE) algorithms with various receive antennas numbers (2Rx, 16Rx, and 32Rx) in relatively low signal-to-noise ratio. A simulation model was developed for block error rate (BLER) evaluation of two test cases with Reed-Muller and Polar codes. Simulation results show that the MMSE algorithm provides the best performance for all considered receive antennas numbers. However, the moving-average LS algorithm should be a suitable choice since it provides a good trade-off between performance and complexity. Finally, it is shown that the energy efficiency of the system can be significantly increased by 12–14 dB when using 32Rx instead of 2Rx. The results in this paper can provide specific system-oriented information for designing and implementing 5G NR systems.