A Semi-Blind Based Channel Estimator for Pilot Contaminated One-Bit Massive MIMO Systems

Abstract

Massive multiple-input multiple-output (MIMO) is a breakthrough technology equipped with a large number of antennas and radio frequency (RF) chains, which increases complexity and circuit power consumption at the RF front-ends. Power utilisation of analog-to-digital converters is a major concern in RF chains, so one-bit massive MIMO systems are seen as one of the potential solutions to this problem. Further, channel state information (CSI) accuracy at the base station is one of the crucial needs for realising the benefits of one-bit massive MIMO. The existing pilot based estimators demand additional pilots for enhancing the CSI accuracy which in turn reduces the spectral efficiency of the system. To address this limitation, we propose an iterative semi-blind based channel estimator for one-bit massive MIMO systems in a pilot contaminated scenario. The proposed algorithm consists of two stages namely, initialisation and iteration. The initial channel estimate is obtained from pilot based initialisation stage, which is further refined in iteration stage with the help of both pilot and a few data symbols. The proposed semi-blind algorithm improves estimation accuracy with minimum number of pilot symbols. Through simulations, we show that the proposed scheme achieves a considerable improvement in mean square error and bit error rate against the existing pilot based estimators at the cost of a nominal increase in computational complexity. Moreover, the proposed algorithm attains convergence in two iterations for all the considered scenarios. The proposed estimator is spectral and power-efficient in comparison to the pilot based algorithms. To the best of our knowledge, it is the first attempt of channel estimation in pilot contaminated one-bit massive MIMO systems.