Channel Estimation and Performance Analysis of One-Bit One Bit Massive MIMO Systems
Abstract: This paper considers channel estimation and system performance for the uplink of a single-cell cell massive multiple-input multiple multiple-output output system. Each receiver antenna of the base station is assumed to be equipped with a pair of one-bit one analog-to-digital converters rters to quantize the real and imaginary part of the received signal. We first propose an approach for channel estimation that is applicable for both flat and frequency-selective frequency selective fading, based on the Bussgang decomposition that reformulates the nonlinear quantizer quantizer as a linear function with identical first- and second-order second order statistics. The resulting channel estimator outperforms previously proposed approaches across all SNRs. We then derive closed-form form expressions for the achievable rate in flat fading channels chann assuming low SNR and a large number of users for the maximal ratio and zero forcing receivers that takes channel estimation error due to both noise and one-bit one quantization into account. The closed closed-form form expressions, in turn, allow us to obtain insight into important system design issues such as optimal resource allocation, maximal sum spectral efficiency, overall energy efficiency, and number of antennas. Numerical results are presented to verify our analytical results and demonstrate the benefit of opt optimizing imizing system performance accordingly.