A Joint Iterative Quantization and Channel Estimation Scheme for One-Bit Massive MIMO Systems

Abstract

We consider the channel estimation problem for uplink multiuser massive MIMO systems with one-bit analog-to-digital converters (ADCs). The problem of optimal one-bit quantization thresholds is studied in this paper. Our analysis reveals that, if the quantization thresholds are optimally devised, using one-bit ADCs can achieve an estimation error close to (only increase by a factor of π/2) that of an ideal clairvoyant estimator using unquantized data. The optimal quantization thresholds, however, are dependent on the unknown channel parameters. To cope with this difficulty, we propose an Iterative Quantization (IQ) approach in which the thresholds are adaptively adjusted in a way such that the thresholds converge to the optimal thresholds. Simulation results show that our proposed iterative quantization scheme presents a similar performance compared with traditional channel estimation with full resolution ADCs.