Energy efficiency of mmWave massive MIMO precoding with low-resolution DACs

Abstract: With the congestion of the sub-6 GHz spectrum, the interest in massive multiple-input multiple-output (MIMO) systems operating on millimeter wave spectrum grows. In order to reduce the power consumption of such massive MIMO systems, hybrid analog/digital transceivers and application of low-resolution digital-to-analog/analog-to-digital converters have been recently proposed. In this work, we investigate the energy efficiency of quantized hybrid transmitters equipped with a fully/partially-connected phase-shifting network composed of active/passive phase-shifters and compare it to that of quantized digital precoders. We introduce a quantized single-user MIMO system model based on an additive quantization noise approximation considering realistic power consumption and loss models to evaluate the spectral and energy efficiencies of the transmit precoding methods. Simulation results show that partially-connected hybrid precoders can be more energy-efficient compared to digital precoders, while fully-connected hybrid precoders exhibit poor energy efficiency in general. Also, the topology of phase-shifting components offers an energy-spectral efficiency trade-off: active phase-shifters provide higher data rates, while passive phase-shifters maintain better energy efficiency.

• The paper introduces a novel additive quantization noise model to realistically evaluate spectral and energy efficiencies in mmWave MIMO systems.
• The paper compares fully- and partially-connected phase-shifting networks, highlighting a trade-off between spectral efficiency with active and energy efficiency with passive phase-shifters.
• The paper employs simulation results to show that partially-connected PSNs can optimize energy consumption while maintaining competitive throughput.

Insights into the Energy Efficiency of mmWave Massive MIMO Precoding with Low-Resolution DACs

The paper under examination focuses on the growing interest in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems, driven in part by the congestion in the sub-6 GHz spectrum. The authors aim to address energy efficiency concerns associated with these systems by exploring hybrid analog/digital transceivers and low-resolution digital-to-analog converters (DACs), noting significant operational challenges within the mmWave spectrum.

System Model and Problem Formulation

The paper provides an in-depth SU-MIMO system model for quantized hybrid precoding, considering fully and partially-connected phase-shifting networks which incorporate either active or passive phase-shifters. The focus is on comparing these hybrid precoding methods with quantized digital precoders. A novel approach to model DAC quantization via an additive quantization noise model is employed, allowing for a realistic evaluation of spectral and energy efficiencies.

Key Insights and Numerical Results

• Quantized Hybrid Precoding Models: The study introduces a generalized problem formulation for quantized hybrid precoding. Notably, the paper outlines achievable rate expressions and challenges posed by RF losses, presenting simulation-driven insights into system performance at various DAC resolutions.
• Phase-Shifting Network Analysis: The results highlight that hybrid precoders with partially-connected PSNs tend to be more energy-efficient than fully-connected configurations, primarily due to reduced power consumption and insertion losses. Additionally, the implementation method of phase-shifters reveals a key trade-off: active phase-shifters improve spectral efficiency, while passive ones enhance energy efficiency.
• Simulated Spectral and Energy Efficiency: The spectral efficiency of the system is shown to be influenced by both the quantization level and the RF hardware model, where passive components tend to underperform in spectral throughput but outperform in energy efficiency metrics.

Computational and Power Consumption Models

On the computational front, the paper presents an analysis of the complexity involved in analog and digital precoding strategies, factoring in operations like singular value decomposition and iterative methods. The power consumption model employed is comprehensive, including computational overhead, RF hardware losses, and static consumption metrics. The results emphasize the importance of computational efficiency in large-array systems.

Theoretical Implications and Future Directions

While the work primarily addresses specific aspects of precoding in mmWave MIMO systems, it opens avenues for further exploration of transceiver architectures. The findings suggest that partially-connected PSNs could be optimal for practical massive MIMO implementations targeting both energy and spectral efficiency. Future research could explore multi-user system configurations, considering interference effects and transceiver optimization under imperfect channel state information.

In summary, the authors effectively balance between a detailed theoretical model and practical simulation results, offering substantive contributions to the study of energy-efficient massive MIMO precoding systems in the mmWave domain. This work is poised to influence future developments in transceiver technologies and optimization strategies for high-frequency wireless communication systems.