Quantization Noise Suppression in Digital Phased Arrays for Millimeter-Wave Communications

Core Concepts

Coherent combining in digital phased arrays can significantly suppress quantization noise, enabling the use of lower-resolution ADCs compared to analog phased arrays.

Abstract

The paper analyzes the quantization noise characteristics for a Gaussian signal received and processed by a digital phased array. It demonstrates that coherent combining of the signals received by the antenna array can lead to substantial quantization noise suppression.
The key highlights and insights are:

Derived an analytical expression for the covariance between the quantization errors of complex Gaussian variables that differ by a phase shift, which is relevant for digital phased arrays receiving OFDM signals.

Quantified the quantization noise suppression factor analytically and numerically as a function of the number of antennas and ADC bit resolution. This factor describes how much the coherent combining reduces the quantization noise.

Showed that in an 8-16 antenna digital phased array, the ADC resolution can be reduced by 1-2 bits compared to the ADC required for an analog phased array, while maintaining similar performance.

Provided insights on the implications of these results for the design of millimeter-wave digital phased array architectures in mobile devices, where the ADC power consumption can be significantly reduced compared to analog phased arrays.

Stats

The ADC power consumption ratio between digital and analog phased array architectures is only a factor of 4, not a factor of 16, when considering the quantization noise suppression in digital phased arrays.

Quotes

"For instance in a 8-16 antenna digital phased array the ADC resolution can be reduced with 1-2 bits compared to the ADC required for an analog phased array."
"The ADC power consumption for the digital architecture is proportional to 16 · 2^k, compared to the analog architecture's 2^(2k). Hence, the ADC power consumption ratio is only a factor of 4, not a factor 16 in this example."

Key Insights Distilled From

Analysis of Quantization Noise Suppression Gains in Digital Phased Arrays

by Erik... at arxiv.org 05-03-2024

https://arxiv.org/pdf/2405.00830.pdf

Deeper Inquiries

How can the quantization noise suppression in digital phased arrays be further improved, for example by leveraging advanced signal processing techniques?

In digital phased arrays, quantization noise suppression can be enhanced through various advanced signal processing techniques. One approach is to implement sophisticated digital signal processing algorithms that can exploit the spatial diversity of signals received by multiple antennas. By utilizing techniques such as beamforming, spatial filtering, and interference cancellation, the system can effectively separate desired signals from noise and interference, leading to improved signal quality and reduced quantization noise impact.
Moreover, adaptive algorithms like adaptive beamforming can dynamically adjust the array's response to changing signal conditions, optimizing the reception and processing of signals. By continuously adapting the array's weights based on the received signals, the system can enhance the signal-to-noise ratio and mitigate the effects of quantization noise.
Furthermore, employing advanced error correction coding schemes and signal processing algorithms can help mitigate the impact of quantization noise. Techniques such as error correction coding, channel equalization, and signal reconstruction can be utilized to recover the original signal from the quantized data more accurately, reducing the distortion introduced by quantization.
Additionally, machine learning and artificial intelligence algorithms can be leveraged to optimize the processing of signals in digital phased arrays. By training models on large datasets of received signals, these algorithms can learn to distinguish between signal and noise patterns, enabling more effective noise suppression and signal recovery.

What are the potential trade-offs and limitations of using lower-resolution ADCs in digital phased arrays, such as impact on dynamic range, linearity, and power efficiency?

While using lower-resolution ADCs in digital phased arrays offers advantages such as reduced power consumption and cost, there are trade-offs and limitations to consider:

Dynamic Range: Lower-resolution ADCs have a limited dynamic range, which can result in reduced ability to capture and distinguish between weak and strong signals. This limitation can lead to signal distortion and reduced system performance, especially in environments with varying signal strengths.

Linearity: Lower-resolution ADCs may exhibit non-linear behavior, causing signal distortion and intermodulation effects. This can impact the accuracy of signal processing algorithms and degrade the overall system performance, particularly in scenarios with high signal complexity.

Signal Fidelity: Decreased ADC resolution can compromise the fidelity of signal representation, leading to quantization errors and reduced signal-to-noise ratio. This can affect the quality of received signals and limit the system's ability to extract useful information from the data.

Power Efficiency: While lower-resolution ADCs consume less power compared to higher-resolution counterparts, they may introduce inefficiencies in signal processing. The need for additional processing to compensate for quantization errors and limitations can offset the power savings achieved by using lower-resolution ADCs.

Sensitivity to Noise: Lower-resolution ADCs are more susceptible to noise and interference, as they have fewer quantization levels to represent the signal accurately. This can result in increased vulnerability to external disturbances and reduced system robustness.

Given the advantages of digital phased arrays, what other system-level design considerations and architectural choices should be explored to enable their widespread adoption in 5G and beyond millimeter-wave communication systems?

To facilitate the widespread adoption of digital phased arrays in 5G and beyond millimeter-wave communication systems, several system-level design considerations and architectural choices should be explored:

Hybrid Beamforming: Implementing hybrid beamforming architectures that combine analog and digital beamforming techniques can enhance the system's flexibility and efficiency. By leveraging the benefits of both approaches, hybrid beamforming can optimize the trade-offs between performance, complexity, and cost.

Advanced Signal Processing: Integrating advanced signal processing algorithms, such as machine learning-based beamforming optimization and interference mitigation techniques, can further enhance the capabilities of digital phased arrays. These algorithms can adaptively optimize array performance in real-time, improving signal quality and system efficiency.

Network Synchronization: Ensuring precise synchronization among array elements and network components is crucial for coherent signal processing and beamforming. Exploring synchronization techniques, such as distributed synchronization algorithms and time-sensitive networking protocols, can improve system performance and reliability.

Energy-Efficient Architectures: Designing energy-efficient architectures by optimizing power consumption at each system component, including ADCs, amplifiers, and processing units, is essential for enabling the deployment of digital phased arrays in energy-constrained environments. Exploring low-power design techniques and energy harvesting solutions can enhance system sustainability.

Interference Management: Developing robust interference management strategies, such as interference cancellation algorithms and spectrum sharing mechanisms, can mitigate the impact of co-channel interference and improve spectral efficiency in dense millimeter-wave communication scenarios. By effectively managing interference, digital phased arrays can achieve higher data rates and improved network capacity.

By addressing these system-level design considerations and architectural choices, digital phased arrays can realize their full potential in 5G and future millimeter-wave communication systems, enabling high-performance, flexible, and energy-efficient wireless networks.