Massive MIMO: Ten Myths and One Critical Question (1503.06854v2)

Abstract: Wireless communications is one of the most successful technologies in modern years, given that an exponential growth rate in wireless traffic has been sustained for over a century (known as Cooper's law). This trend will certainly continue driven by new innovative applications; for example, augmented reality and internet-of-things. Massive MIMO (multiple-input multiple-output) has been identified as a key technology to handle orders of magnitude more data traffic. Despite the attention it is receiving from the communication community, we have personally witnessed that Massive MIMO is subject to several widespread misunderstandings, as epitomized by following (fictional) abstract: "The Massive MIMO technology uses a nearly infinite number of high-quality antennas at the base stations. By having at least an order of magnitude more antennas than active terminals, one can exploit asymptotic behaviors that some special kinds of wireless channels have. This technology looks great at first sight, but unfortunately the signal processing complexity is off the charts and the antenna arrays would be so huge that it can only be implemented in millimeter wave bands." The statements above are, in fact, completely false. In this overview article, we identify ten myths and explain why they are not true. We also ask a question that is critical for the practical adoption of the technology and which will require intense future research activities to answer properly. We provide references to key technical papers that support our claims, while a further list of related overview and technical papers can be found at the Massive MIMO Info Point: http://massivemimo.eu

• The paper systematically debunks ten prevalent myths about Massive MIMO using both empirical evidence and theoretical analysis.
• It demonstrates that leveraging large antenna arrays enhances signal strength and reduces interference even under typical cellular conditions.
• The study raises a critical question on FDD feasibility, prompting further research into efficient CSI acquisition and sparsity-exploiting methods.

Overview of "Massive MIMO: Ten Myths and One Critical Question" by Björnson, Larsson, and Marzetta

The paper entitled “Massive MIMO: Ten Myths and One Critical Question” by Emil Björnson, Erik G. Larsson, and Thomas L. Marzetta addresses common misconceptions regarding Massive MIMO (multiple-input multiple-output) technology in wireless communications, alongside raising a pivotal question about its feasibility in Frequency Division Duplex (FDD) operations. This document aims to clarify misunderstandings, supported by empirical and theoretical evidence.

Massive MIMO, characterized by equipping each base station (BS) with a large number of antennas to serve multiple single-antenna terminals, significantly enhances wireless communication capacity and reliability. By focusing the transmission and reception of signals via coherent processing over the antenna array, Massive MIMO mitigates interference and increases signal strength through array gain. This paper asserts that although Massive MIMO is touted for its potential, it is often misunderstood.

Debunking the Myths

The authors demystify ten prevalent myths surrounding Massive MIMO:

1. Suitability for Millimeter Wave Bands: The paper refutes the claim that Massive MIMO can only operate effectively in millimeter-wave frequencies. It demonstrates that practical antenna arrays can be deployed even at typical cellular frequencies like 2 GHz with scalable and feasible form factors.
2. Operational Environment Assumptions: Contrary to the notion that Massive MIMO requires rich-scattering environments, the paper shows that both line-of-sight (LoS) and non-line-of-sight (non-LoS) environments can effectively leverage this technology.
3. Comparison with Open-Loop Beamforming: The performance achievable through open-loop beamforming (OLB) is limited compared to Massive MIMO. Empirical results substantiate that CSI-based massive MIMO consistently outperforms OLB, particularly as the number of antennas increases.
4. Dependence on Asymptotic Results: The authors argue that while initial studies focused on asymptotic behavior, numerous follow-up works have derived finite-dimension closed-form expressions that are valid for practical configurations, proving that significant gains are achievable even with a finite number of antennas and terminals.
5. Performance of Linear Processing Techniques: The magnitude of performance loss due to linear processing methods (e.g., Zero-Forcing) compared to optimal non-linear techniques (e.g., Dirty Paper Coding) diminishes significantly as the number of antennas increases. Importantly, linear methods are computationally less complex and thus practical.
6. Necessitating an Order of Magnitude More Antennas: While a larger number of antennas relative to users is beneficial, the performance gains are substantial even when the number of antennas is only a few times larger than the number of users.
7. Inability of New Terminals to Join: The concern that Massive MIMO cannot accommodate new terminals due to lack of initial array gain is dismissed. The authors explain methods such as control signals for pilot-based access enabling straightforward integration of new terminals.
8. Requirement for High Precision Hardware: The system is robust to hardware impairments, and the paper explains how the coherent processing in Massive MIMO mitigates distortions from low-precision hardware.
9. Resource Allocation Complexity: The perception that resource allocation and power control become overly complex with many antennas is refuted. The authors show that the channel hardening effect simplifies these tasks significantly, often reducing them to simple long-term power control problems.
10. Overwhelming Signal Processing Complexity: Despite the large number of antennas, the computational complexity remains manageable. The scaling of computations such as FFT, channel estimation, and linear processing operations is linear, making state-of-the-art implementations feasible under contemporary technology constraints.

The Critical Question: FDD Feasibility

One critical question addressed is whether Massive MIMO can be effectively implemented in FDD mode. While TDD (Time Division Duplex) mode exploits channel reciprocity to reduce CSI acquisition overhead, FDD mode does not, resulting in greater challenges. The paper illustrates that in high-mobility or high-frequency scenarios, the overhead in FDD becomes intractable compared to TDD, especially as the coherence interval shrinks.

To address this, researchers have proposed sparsity-exploiting methods to reduce overhead in FDD. However, the assumptions underlying these methods, such as spatial sparsity, require further validation through measurements, particularly at lower frequencies where such assumptions may not hold. Proof-of-concept implementations and channel measurements are essential for determining the feasibility of Massive MIMO in FDD systems.

Implications and Future Research

The implications of this paper are multifaceted. Practically, it provides clarity on the operational conditions and configurations suitable for deploying Massive MIMO. Theoretically, it encourages exploration into the sparsity of channel responses which could unlock additional efficiencies in FDD mode. It also propels future research into advanced signal processing techniques and hardware designs that align with the expected deployment scenarios of 5G and beyond.

In conclusion, Björnson, Larsson, and Marzetta deliver a comprehensive analysis that dispels prevalent myths about Massive MIMO and calls for focused research on the unresolved challenges, particularly regarding FDD operation. Their insights pave the way for more informed development and deployment of this pivotal technology in next-generation wireless communication networks.