Achieving Near Capacity of Non-Binary LDPC Coded Large MIMO Systems with a Novel Ultra Low-Complexity Soft-Output Detector

Suthisopapan, Puripong; Kasai, Kazuhiko; Meesomboon, Anupap; Imtawil, Virasit

doi:10.1109/twc.2013.090513.122056

Cited by 16 publications

(5 citation statements)

References 38 publications

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“…Additionally, they applied various detectors, including the MMSE detector, the PDA detector, the LAS detector and the RTS detector, in high-rate non-orthogonal STBC aided LS-MIMO systems [128], [328], [329]. Furthermore, it was shown that non-binary LDPC coded LS-MIMO systems are capable of achieving a near-capacity performance with MMSE detection [336]. It should be noted that in principle a variety of other metaheuristics based MUDs, such as the genetic algorithm (GA) based MUD [529]- [535], the ant colony optimization (ACO) based MUD [537]- [541], the particle swarm optimization (PSO) aided MUD [545]- [547], and the simulated annealing (SA) assisted MUD [548], [549], may also be extended to the LS-MIMO context.…”

Section: Recent Advances In Ls-mimo Detectionmentioning

confidence: 99%

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

Yang

Hanzo

2015

IEEE Commun. Surv. Tutorials

698

439

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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.Comment: 51 pages, 36 figures, 10 tables, 659 references, accepted to appear on IEEE Communications Surveys & Tutorials, June 201

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Section: Recent Advances In Ls-mimo Detectionmentioning

confidence: 99%

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

Yang

Hanzo

2015

IEEE Commun. Surv. Tutorials

698

439

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“…Following are some examples. Modified MMSE and matched filter (MF) soft-output detection [45] and the FG-based BP detection with Gaussian approximation of interference (FG-GAI BP) [37], [46], [47] were considered in designing LDPC codes for massive MIMO systems. Iterative soft-input soft-output (SISO) MMSE detectors were proposed to enhance the signal detection of massive MIMO systems [17]- [21].…”

Section: Introductionmentioning

confidence: 99%

Design of LDPC Coded Multi-User Massive MIMO Systems With MMSE-Based Iterative Joint Detection and Decoding

Park,

Lee

2023

IEEE Access

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We design a low-density parity-check (LDPC) coded multi-user massive multiple-input multiple-output (MIMO) system to achieve a high error correcting capability with a fast convergence speed of iterative joint detection and decoding (JDD) process employing a low-complexity detection. Minimum mean squared error detection with parallel interference cancellation (MMSE-PIC) and its variations are considered as low-complexity linear detection algorithms. We provide a factor graph representation of LDPC coded multi-user massive MIMO system using JDD algorithm employing MMSE-PIC detection, and we formulate updating rules of messages flowing in the JDD process. We propose a practical and efficient tool for analyzing the extrinsic information transfer (EXIT) characteristics of messages exchanged between detector and decoder, based on which LDPC codes and JDD strategy are jointly designed to result in a low bit error rate (BER) and a fast convergence speed of JDD mechanism. It is observed that the error correcting capability and JDD convergence behavior predicted by the proposed analysis tool match well the actual performances obtained by simulations. It is also observed that LDPC coded multi-user massive MIMO system employing LDPC codes and JDD strategy designed optimally by the proposed EXIT analysis tool achieves a lower BER with a faster convergence speed.INDEX TERMS Coded multi-user massive-MIMO, LDPC codes, joint detection and decoding, MMSE-PIC, EXIT analysis.

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“…Since decoding process requires additional computational complexity, a low-complexity detection algorithm had better be applied to JDD. In [30], non-binary LDPC codes are designed for coded massive MIMO systems considering modified MMSE and matched filter (MF) soft-output detectors. In [31]- [33], binary and non-binary LDPC codes for massive MIMO systems using the FG-GAI BP detection are designed.…”

Section: Introductionmentioning

confidence: 99%

LDPC Coded Multi-User Massive MIMO Systems With Low-Complexity Detection

Park

Lee

2022

IEEE Access

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We design a low-density parity-check (LDPC) coded multi-user (MU) massive multipleinput multiple-output (MIMO) system with an iterative joint detection and decoding (JDD) algorithm. As a low-complexity MU detection scheme, we consider a factor graph based belief propagation detection with Gaussian approximation of interference, called a FG-GAI BP detection. We introduce a factor graph representation of LDPC coded MU massive MIMO system and define the message updating rule in the JDD process. We devise a design tool for analyzing extrinsic information transfer (EXIT) characteristics of messages exchanged in JDD, based on which degree distribution of LDPC codes and a JDD strategy are efficiently designed for coded MU massive MIMO systems. A JDD strategy and LDPC codes are designed such that a fast convergence of JDD and a low bit error probability are attained. It is observed that the coded MU massive MIMO system equipped with LDPC codes and the JDD strategy designed by the proposed method shows a lower bit error rate than conventional ones with a given number of iterations.

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Achieving Near Capacity of Non-Binary LDPC Coded Large MIMO Systems with a Novel Ultra Low-Complexity Soft-Output Detector

Cited by 16 publications

References 38 publications

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

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

Design of LDPC Coded Multi-User Massive MIMO Systems With MMSE-Based Iterative Joint Detection and Decoding

LDPC Coded Multi-User Massive MIMO Systems With Low-Complexity Detection

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