Uplink Performance of Time-Reversal MRC in Massive MIMO Systems Subject to Phase Noise (1306.4495v2)

Abstract: Multi-user multiple-input multiple-output (MU-MIMO) cellular systems with an excess of base station (BS) antennas (Massive MIMO) offer unprecedented multiplexing gains and radiated energy efficiency. Oscillator phase noise is introduced in the transmitter and receiver radio frequency chains and severely degrades the performance of communication systems. We study the effect of oscillator phase noise in frequency-selective Massive MIMO systems with imperfect channel state information (CSI). In particular, we consider two distinct operation modes, namely when the phase noise processes at the $M$ BS antennas are identical (synchronous operation) and when they are independent (non-synchronous operation). We analyze a linear and low-complexity time-reversal maximum-ratio combining (TR-MRC) reception strategy. For both operation modes we derive a lower bound on the sum-capacity and we compare their performance. Based on the derived achievable sum-rates, we show that with the proposed receive processing an $O(\sqrt{M})$ array gain is achievable. Due to the phase noise drift the estimated effective channel becomes progressively outdated. Therefore, phase noise effectively limits the length of the interval used for data transmission and the number of scheduled users. The derived achievable rates provide insights into the optimum choice of the data interval length and the number of scheduled users.

• The paper analyzes the impact of oscillator phase noise on uplink performance in massive MIMO systems using time-reversal maximum-ratio combining (TR-MRC).
• Analysis shows TR-MRC achieves an O(√M) array gain and that independent phase noise sources may potentially yield higher sum-rates.
• Findings reveal a fundamental trade-off in data transmission interval length versus sum-rate due to phase drift, offering insights for practical optimization.

Overview of Uplink Performance of Time-Reversal MRC in Massive MIMO Systems Subject to Phase Noise

The discussed paper presents a comprehensive analysis of the uplink performance in massive multiple-input multiple-output (MIMO) systems, specifically addressing the impact of oscillator phase noise. Massive MIMO, characterized by a large array of base station (BS) antennas, promises substantial multiplexing gains and improved energy efficiency. However, these systems are susceptible to oscillator phase noise inherent in the transmitter and receiver radio frequency chains, affecting overall communication efficacy.

Key Contributions

The authors focus specifically on frequency-selective massive MIMO systems where channel state information (CSI) is not perfect. They propose and analyze a time-reversal maximum-ratio combining (TR-MRC) reception strategy—a linear technique favorable for its low complexity. Their research evaluates two operation modes considering the phase noise processes:

• Synchronous operation: All BS antennas experience identical phase noise processes.
• Non-synchronous operation: Each BS antenna has independent phase noise processes.

For both modes, a lower bound on the sum-capacity is derived, and their performances are juxtaposed. The TR-MRC strategy demonstrates the potential to achieve an $O(\sqrt{M})$ array gain, indicating significant power scaling benefits with increased antennas.

Analysis and Results

The paper provides analytical expressions for achievable sum-rates, showing that for a constant per-user information rate, one can reduce the total transmit power by a factor of $\sqrt{2}$ with doubling the BS antennas. This aligns with existing scaling laws observed in systems without phase noise. Additionally, it is revealed that using independent phase noise sources could potentially yield higher sum-rate performance, supported by a toy example illustrating capacity behavior under different noise settings.

Essentially, phase noise impairs the system by introducing drift, which progressively erodes the accuracy of the effective channel estimation during data transmission intervals. Notably, the analysis highlights:

• Low-SNR regime robustness: Phase noise has minimal impact at low signal-to-noise ratios.
• High-SNR saturation: At high SNR values, interference dominates, resulting in rate saturation.
• Power scaling: An $O(\sqrt{M})$ array gain is achievable, extending known principles from Massive MIMO contexts.
• Training trade-off: The results underscore a fundamental trade-off in the length of data transmission intervals versus sum-rate performance due to phase drift.
• Optimization insights: Insights into optimal data interval length and user scheduling are provided, vital for operational efficiency in practical applications.

Practical and Theoretical Implications

The findings offer significant implications for the design and deployment of massive MIMO systems. Practically, the insights are useful for optimizing oscillator quality versus quantity to balance system performance economically. From a theoretical standpoint, the results extend fundamental Massive MIMO theories to include phase noise, supporting realistic, robust design frameworks.

Future Directions

Continued research could focus on further optimizing TR-MRC strategies for varying degrees of channel state imperfections and more complex phase noise models. Integration with advanced hardware compensation techniques and exploring cross-layer design considerations remain promising avenues to mitigate phase noise impacts comprehensively.

Ultimately, this paper contributes to the ongoing discourse on reliable massive MIMO communication systems by establishing a nuanced understanding of phase noise impacts and articulating practical strategies to harness Massive MIMO's full potential despite inherent deviations in the baseband signal processing chain.