Fifty Years of MIMO Detection: The Road to Large-Scale MIMOs (1507.05138v1)

Abstract: The emerging massive/large-scale MIMO (LS-MIMO) systems relying on very large antenna arrays have become a hot topic of wireless communications. Compared to the LTE based 4G mobile communication system that allows for up to 8 antenna elements at the base station (BS), the LS-MIMO system entails an unprecedented number of antennas, say 100 or more, at the BS. The huge leap in the number of BS antennas opens the door to a new research field in communication theory, propagation and electronics, where random matrix theory begins to play a dominant role. In this paper, we provide a recital on the historic heritages and novel challenges facing LS-MIMOs from a detection perspective. Firstly, we highlight the fundamentals of MIMO detection, including the nature of co-channel interference, the generality of the MIMO detection problem, the received signal models of both linear memoryless MIMO channels and dispersive MIMO channels exhibiting memory, as well as the complex-valued versus real-valued MIMO system models. Then, an extensive review of the representative MIMO detection methods conceived during the past 50 years (1965-2015) is presented, and relevant insights as well as lessons are inferred for designing complexity-scalable MIMO detection algorithms that are potentially applicable to LS-MIMO systems. Furthermore, we divide the LS-MIMO systems into two types, and elaborate on the distinct detection strategies suitable for each of them. The type-I LS-MIMO corresponds to the case where the number of active users is much smaller than the number of BS antennas, which is currently the mainstream definition of LS-MIMO. The type-II LS-MIMO corresponds to the case where the number of active users is comparable to the number of BS antennas. Finally, we discuss the applicability of existing MIMO detection algorithms in LS-MIMO systems, and review some of the recent advances in LS-MIMO detection.

Fifty Years of MIMO Detection: The Road to Large-Scale MIMOs

The paper, authored by Shaoshi Yang and Lajos Hanzo, encompasses fifty years of advancements in multiple-input multiple-output (MIMO) detection, focusing on the transition to large-scale MIMO (LS-MIMO) systems. As cellular networks evolve, the emergence of LS-MIMO systems marks a significant progression in wireless communication. These systems employ extensive antenna arrays, allowing them to handle exponentially more data traffic given the increasing demand from global mobile networks and the inherent limitations of radio spectrum.

Overview

The transformation from traditional MIMO systems, observed in earlier generations (2G, 3G, 4G), to LS-MIMO anticipates the needs of upcoming 5G systems. Unlike current systems where up to eight antennas are typical, LS-MIMO involves deploying hundreds of antennas. This stark increase in the volume of antennas introduces substantial qualitative changes driven by quantitative leaps, which the authors explain through the lens of random matrix theory and its growing dominance in characterizing these systems.

Detection Perspectives

The paper meticulously outlines the challenges and strategies in MIMO detection over the past half-century. It commences with foundational concepts, describing co-channel interference, signal models like linear memoryless and dispersive channels, and contrasting complex-valued versus real-valued system models. These underpin the understanding crucial for developing algorithms tailored to LS-MIMO's detection needs.

Historical Context and Classification

The evolution of MIMO detection is segmented chronologically:

• Early Developments (1960s-70s): Initial efforts focused on combatting crosstalk and intersymbol interference in TDM/FDM systems.
• Multiuser Detection Era (1980s-90s): The growth of CDMA systems necessitated multiuser detectors (MUDs) for efficient interference management.
• Rise of Small/Medium-Scale MIMOs (Mid-1990s-2000s): This period saw a surge in joint detection techniques for antennas prevalent in then-contemporary MIMO systems.
• Development Towards LS-MIMOs: The recent focus has shifted towards scalable detection algorithms suitable for LS-MIMO systems.

Different MIMO detectors are discussed, such as linear, interference cancellation, tree-search based, probabilistic data association, and semidefinite programming relaxation techniques. Each class of detector is evaluated concerning computational complexity and error rate performance. For instance, while optimal maximum likelihood detectors are computationally prohibitive, advancements like sphere decoding offer feasible alternatives with reduced complexity.

Modern Challenges and Applications

The paper pays detailed attention to LS-MIMO systems, especially the configurations of Type-I and Type-II systems. It highlights the distinctions in detection strategies and complexities between single-cell, multi-cell non-cooperative, and cooperative multi-cell setups. In particular:

• Type-I Systems: Characterized by a comparable number of transmit and receive antennas, facilitating a deterministic limiting distribution due to the Marčenko-Pastur law.
• Type-II Systems: Marked by a disparity in the number of antennas favoring the receiver, leading to robust performance that can even allow matched filter techniques to approach optimality.

Theoretical and Practical Implications

From practical perspectives, LS-MIMO systems promise enhancements in spectral and energy efficiency. Theoretically, they induce substantial changes in signal processing approaches, demanding new detection algorithms that scale with the system size. The paper suggests methods such as iterative Bayesian detection and soft-output detectors to meet these challenges.

Future Directions

As 5G and beyond become successful, LS-MIMO systems will become cornerstones of cellular infrastructures. Future research, speculated by the authors, may delve into even more scalable solutions, advanced channel state information sharing, and novel coding strategies optimized for LS-MIMO configurations.

Conclusion

In summation, this treatise on MIMO detection draws a comprehensive arc over five decades, signifying a crucial moment in heralding LS-MIMO as a future-proof technology for burgeoning wireless applications. The paper signifies not only a milestone in MIMO research but also sets a clear trajectory toward embracing large-scale antenna systems as a standard, underscoring both the historical depth and forward-looking vision of these advancements.