Throughput Analysis of Massive MIMO Uplink with Low-Resolution ADCs (1602.01139v3)

Abstract: We investigate the uplink throughput achievable by a multiple-user (MU) massive multiple-input multiple-output (MIMO) system in which the base station is equipped with a large number of low-resolution analog-to-digital converters (ADCs). Our focus is on the case where neither the transmitter nor the receiver have any a priori channel state information. This implies that the fading realizations have to be learned through pilot transmission followed by channel estimation at the receiver, based on coarsely quantized observations. We propose a novel channel estimator, based on Bussgang's decomposition, and a novel approximation to the rate achievable with finite-resolution ADCs, both for the case of finite-cardinality constellations and of Gaussian inputs, that is accurate for a broad range of system parameters. Through numerical results, we illustrate that, for the 1-bit quantized case, pilot-based channel estimation together with maximal-ratio combing or zero-forcing detection enables reliable multi-user communication with high-order constellations in spite of the severe nonlinearity introduced by the ADCs. Furthermore, we show that the rate achievable in the infinite-resolution (no quantization) case can be approached using ADCs with only a few bits of resolution. We finally investigate the robustness of low-ADC-resolution MU-MIMO uplink against receive power imbalances between the different users, caused for example by imperfect power control.

• The paper introduces a novel channel estimator leveraging Bussgang's theorem to approximate achievable rates with low-resolution ADCs.
• It demonstrates that high-order constellations like 16-QAM can be reliably decoded even with severe ADC quantization constraints.
• Numerical analysis confirms that ADC resolutions as low as 3 bits yield throughput close to infinite-resolution scenarios, reducing cost and power consumption.

Analysis of Throughput in Massive MIMO Uplink Systems with Low-Resolution ADCs

The paper provides a comprehensive paper of the uplink throughput capabilities of multi-user massive MIMO systems, focusing on scenarios where base stations integrate low-resolution ADCs. Unlike conventional setups that assume high-resolution data conversion, this investigation assumes neither preliminary channel state information (CSI) at the transmitter nor the receiver—requiring channel estimation through pilot signals based on quantized observations.

Key Contributions and Methods

The paper introduces a novel channel estimator utilizing Bussgang's theorem, which assists in accurately approximating achievable rates for systems leveraging finite-resolution ADCs across both finite-cardinality constellations and Gaussian inputs. Focusing particularly on 1-bit quantization, the paper illustrates that high-order constellations such as 16-QAM can be successfully decoded despite ADC-induced nonlinearity. This discovery aligns with empirical results demonstrating that even few-bit resolutions suffice in achieving throughput approaching infinite-resolution scenarios, especially when employing ZF or MRC detection methods.

The channel estimation methodology incorporates LMMSE approaches retooled for scenarios with minimal bit quantization, ensuring robustness to power imbalances as well—a common challenge in uplink MIMO systems with limited power control.

Numerical Results and Implications

The paper details an extensive numerical analysis verifying that usable throughput can be efficiently extracted with ADC resolutions as low as 3 bits, thus offering substantial cost and power savings over traditional architectures using higher-bit ADCs. This represents a compelling shift in how future 5G and beyond systems could be architected driverously lowering power and financial constraints inherent to massive MIMO deployments.

Future Considerations

The implications of these findings are substantial, suggesting a pathway for more efficient MIMO system deployments which economize on hardware requirements without sacrificing communication quality. Future work might extend to address wideband systems using OFDM, leveraging this investigation's insights into reducing ADC overhead at larger bandwidths and in multi-path interference environments.

Ultimately, the research provides a substantive foundation that potentially transforms how massive MIMO uplinks can be implemented, setting a new standard for balancing performance against cost and power efficiency in modern wireless systems.