Performance Analysis of Massive MIMO Relay Systems With Variable-Resolution ADCs/DACs Over Spatially Correlated Channels

The use of low-resolution analog-to-digital converters (ADCs) and digital-to-analog converters (DACs) is recognized as a practical technique to reduce power consumption and hardware cost for massive multiple-input and multiple-output (MIMO) systems. In this context, by leveraging on the additive quantization noise model (AQNM), this paper investigates the performance of massive MIMO relay systems with a variable-resolution ADC/DAC-based architecture, where each ADC and DAC use arbitrary bits for quantization. To be specific, we first derive the closed-form expression of achievable rate over spatially correlated Rayleigh fading channels by using perfect channel state information (CSI), maximal ratio combining (MRC), and maximal ratio transmission (MRT). Afterwards, we extend the work to the case of imperfect CSI. The analytical expressions reveal some insights of key parameters, i.e., spatial channel correlation, large-scale fading coefficients, estimate errors, and the resolution of ADCs/DACs. Finally, simulation results validate our theoretical analyses and confirm that the achievable rate reduces as the spatial correlation rises. Besides, we provide the condition under which coarse DACs (ADCs) and receive spatial correlation (transmit spatial correlation) dominate the loss of achievable rate. Moreover, provided that the total number of quantization bits is constant, we find that the achievable rate is optimal over spatially correlated channels when all ADC and DAC adopt the same quantization bits from the perspective of statistic.