Performance Analysis and Transceiver Design of Few-Bit Quantized MIMO Systems

Utilizing low-resolution analog-to-digital converters (ADCs) was proven to be efficient in releasing the burden of power consumption for future wireless systems. In this paper, we analyze and optimize the achievable rate of the multi-input multi-output channel with low-resolution ADCs at the receiver by assuming that the channel state information is known at both the transmitter and the receiver. Toward this end, we first derive the approximate achievable rate of the considered channel model by exploiting the Bussgang theorem. According to the derived achievable rate expression, we propose two approaches, namely, the singular value decomposition-based approach and the gradient-based approach, to jointly optimize the transmit signal covariance and the receive analog combiner. Moreover, an upper bound of achievable rate is derived from the information theory point of view to evaluate the optimality of the derived achievable rate. Extensive simulation results are provided to assess the performance of the proposed designs. We show that the proposed designs can reach the upper bound at low signal-to-noise ratio (SNR), which implies that our optimized achievable rate approaches the capacity at low SNR.