Dynamic ADC Resolution-Mapping for Millimeter-Wave Massive MIMO Systems

Abstract

The radio-frequency (RF) chains, phase shifters (PSs), and analog-to-digital converters (ADCs) play the dominant role of power consumption in the uplink hybrid millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) networks. To mitigate power consumption, an energy-efficient switch and inverter (SI) based partially-connected (PC) architecture with the Gram-Schmidt (GS) antenna selection strategy is addressed. The design of a variable-resolution ADC configuration is addressed under an independent upper bound of power consumption for each ADC in this paper. However, the resulting ADC resolution mapping becomes more complicated due to variant ADC power bounds. A simple ADC bit-allocation algorithm, namely, the sum-resolution (SR) ADC, is proposed. By replacing the total power constraint on ADCs to improve both the achievable sum-rate (ASR) and energy efficiency (EE) performance of the hybrid mmWave massive MIMO system. The SR-ADC solutions in closed form reveal that the optimal ADC resolution is proportional to the square power of the signal-to-noise ratio (SNR) in RF chains. Simulation results demonstrate that the proposed SR-ADC approach offers enhanced improvements on the ASR and EE, and exhibits prominent advantages on the number of activated RF chains compared with the fixed total power system.

Keywords

• ADC
• energy efficiency
• massive MIMO
• mmWave
• partially-connected architecture