Mixed-ADC Massive MIMO

Abstract: Motivated by the demand for energy-efficient communication solutions in the next generation cellular network, a mixed-ADC architecture for massive multiple input multiple output (MIMO) systems is proposed, which differs from previous works in that herein one-bit analog-to-digital converters (ADCs) partially replace the conventionally assumed high-resolution ADCs. The information-theoretic tool of generalized mutual information (GMI) is exploited to analyze the achievable data rates of the proposed system architecture and an array of analytical results of engineering interest are obtained. For fixed single input multiple output (SIMO) channels, a closed-form expression of the GMI is derived, based on which the linear combiner is optimized. The analysis is then extended to ergodic fading channels, for which tight lower and upper bounds of the GMI are obtained. Impacts of dithering and imperfect channel state information (CSI) are also investigated, and it is shown that dithering can remarkably improve the system performance while imperfect CSI only introduces a marginal rate loss. Finally, the analytical framework is applied to the multi-user access scenario. Numerical results demonstrate that the mixed-ADC architecture with a relatively small number of high-resolution ADCs is able to achieve a large fraction of the channel capacity of conventional architecture, while reduce the energy consumption considerably even compared with antenna selection, for both single-user and multi-user scenarios.

• The paper demonstrates that integrating one-bit and high-resolution ADCs in massive MIMO systems sustains high data rates while reducing energy consumption.
• It uses generalized mutual information to derive closed-form and bounded performance expressions for SIMO and ergodic fading channels.
• Results show significant energy efficiency gains and robust multi-user performance, highlighting the architecture’s potential for next-generation cellular networks.

Overview of "Mixed-ADC Massive MIMO"

The paper "Mixed-ADC Massive MIMO" by Ning Liang and Wenyi Zhang offers a comprehensive analysis of a mixed analog-to-digital converter (ADC) architecture for massive multiple input multiple output (MIMO) systems aimed at enhancing energy efficiency, particularly relevant for future cellular networks. Unlike traditional approaches that predominantly rely on high-resolution ADCs, this work innovatively incorporates one-bit ADCs to partially replace the high-resolution ones within the massive MIMO framework.

Key Insights and Methodology

The authors leverage the concept of generalized mutual information (GMI) to evaluate the performance and achievable data rates of the mixed-ADC architecture. This approach allows for an analytical understanding of the system’s capabilities across different channel conditions:

1. Fixed SIMO Channels: The paper derives a closed-form expression of GMI for single input multiple output (SIMO) channels under the proposed architecture. Here, the optimal linear combiner is also formulated, aimed at maximizing the achievable data rates.
2. Ergodic Fading Channels: The study extends the framework to ergodic fading channels and provides tight lower and upper bounds on the GMI. This extension is crucial for understanding real-world applications where fading is inherent.
3. Impact of Dithering and CSI: It is demonstrated that dithering can significantly mitigate the performance degradation caused by quantization errors. Moreover, imperfections in channel state information (CSI) are shown to result in only slight rate losses, suggesting a degree of robustness in the architecture.
4. Multi-user Scenarios: The analysis is further broadened to encompass multi-user access, where the architecture's efficacy in handling simultaneous transmissions from multiple users is tested.

Numerical Results and Practical Implications

Numerical results presented in the paper underscore that a mixed-ADC architecture—with even a small fraction of high-resolution ADCs—can achieve a substantial part of the channel capacity offered by a conventional high-resolution architecture. This is accomplished with marked reductions in energy consumption, presenting a compelling case for practical deployment.

1. Energy Efficiency: The mixed-ADC setup can achieve significant reductions in energy usage compared to both conventional architectures and traditional antenna selection strategies. Notably, when spectral efficiency is minimally compromised, energy consumption is substantially minimized—linked to reduced ADC power requirements.
2. Robustness in Multi-user Environments: The architecture outperforms standard antenna selection in multi-user scenarios by delivering higher spectral efficiencies, particularly relevant as the number of users and antennas increase.

Future Directions

The mixed-ADC approach proposes a well-founded balance between performance and energy efficiency, but several avenues remain open for exploration:

• Optimal ADC Switching Strategies: Developing more sophisticated algorithms to determine optimal switching schemes across various SNR levels and operational conditions.
• Integration with CSI Estimation: Enhancing CSI acquisition using both one-bit and high-resolution ADCs could further bolster system robustness and efficiency.
• Extension to Wideband Scenarios: Addressing frequency-selective channels typical in wideband communications will broaden the practical applicability of this architecture to include scenarios involving OFDM and other multicarrier systems.

In conclusion, this research contributes a significant stepping stone towards realizing more sustainable and efficient communication systems, aligning with the increasing demand for data-intensive applications in next-generation cellular networks.