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

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.

51 pages, 36 figures, 10 tables, 659 references, accepted to appear on IEEE Communications Surveys & Tutorials, June 2015

References in corpus (10)

• Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks
• Large-Scale MIMO Detection for 3GPP LTE: Algorithms and FPGA Implementations
• Quantum-assisted and Quantum-based Solutions in Wireless Systems
• An ESPRIT-Based Approach for 2-D Localization of Incoherently Distributed Sources in Massive MIMO Systems
• On the Capacity of a Class of MIMO Cognitive Radios
• Degrees of Freedom Region for the MIMO X Channel
• Approximate Bayesian Probabilistic-Data-Association-Aided Iterative Detection for MIMO Systems Using Arbitrary M-ary Modulation
• Optimal Spectrum Sharing in MIMO Cognitive Radio Networks via Semidefinite Programming
• Low-Complexity Near-ML Decoding of Large Non-Orthogonal STBCs using Reactive Tabu Search
• Near ML detection using Dijkstra's algorithm with bounded list size over MIMO channels

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