Adaptive-bit Quantized Massive MIMO Systems with MMSE-based Variational Approximate Message Passing

Abstract

Millimeter Wave (Mm Wave) massive multiple-input multiple-output (MIMO) has become an advantageous technology for gigabit-per-second data transmission in 5G wireless communication. To achieve low-cost and energy-efficient hardware components, one-bit quantized massive MIMO systems have been proposed for the receiver hardware architecture. The main focus of this work is leveraging the advantages of a state of the art one-bit quantized massive MIMO system for design of an adaptive-bit massive MIMO system. Hence, in this work, by leveraging the benefits of variational approximate message passing (VAMP), a novel MMSE-based VAMP algorithm is proposed for the adaptive-bit quantized massive MIMO system. That is, two novel modules, i.e., an adaptive ADC bit allocation method and an MMSE-based VAMP, are proposed for mm Wave communications of the hybrid MIMO receiver architecture. With the MMSE-based VAMP, our adaptive ADC bit allocation method is able to decrease the quantization of signals distortion by improving the flexible resolutions of ADC. Through simulations, compared with existing works, our proposed adaptive ADC bit allocation algorithm, together with MMSE-based VAMP, is able to achieve higher capacity, sum rate, and energy efficiency in most communication architectures.