An EXIT Chart Analysis for Belief-Propagation Based Detection in a Large-Scale MIMO System

Takashi, Abiko; Fukuda, Wataru; Nishimura, Toshihiko; Ohgane, Takeo; Ogawa, Yasutaka; Ohwatari, Yusuke; Kishiyama, Yoshihisa

doi:10.1109/vtcspring.2013.6691877

Cited by 5 publications

(6 citation statements)

References 6 publications

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“…We achieve the result in (23) with assumption that the interference plus noise components z[n, m] is approximated i.i.d complex Gaussian random variable. For the high-resolution case, it was verified by both EXIT chart analysis and simulation result that this assumption is reasonable when the number of receive antenna is large [27].…”

Section: ) Mutual Information I α [N M]mentioning

confidence: 81%

“…In [16], the authors illustrated that the channel LLR messages do not follow a symmetric Gaussian distribution in the case of a SIMO Rayleigh fading channel. However, it is not the case for the LS-MIMO systems because each channel LLR message, which is expressed in (27), is a sum of N LLR messages from N observation nodes. As a result, leveraging the law of large number, it is reasonable to assume that channel LLR messages follow a symmetric Gaussian distribution.…”

Section: ) Mutual Information Flow From Variable Nodes To Check Nodesmentioning

confidence: 99%

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Performance Analysis of Protograph LDPC Codes Over Large-Scale MIMO Channels With Low-Resolution ADCs

Nguyen¹,

Vu²,

Nguyen

et al. 2019

IEEE Access

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Protograph LDPC (P-LDPC) codes and large-scale multiple-input multiple-output (LS-MIMO) are cornerstones of 5G and future wireless systems, thanks to their powerful error-correcting capability and high spectral efficiency. To alleviate the high complexity in signal detection/decoding that dramatically grows with the number of antennas (in the order of tens or even hundreds), low-resolution analog-to-digital converters (ADCs) and joint detection and decoding using factor graph have recently attracted paramount interest. Unlike high-resolution ADCs, by using a small number of bits to quantize the received signal, lowresolution ADCs help reduce the hardware cost and power consumption of the RF circuit of practical LS-MIMO transceivers. Such a very much desirable reduction comes at the cost of additional quantization noise, introduced by low-resolution ADCs. This work aims to provide a unified framework to analyze the impact of the low-resolution ADCs on the performance of P-LDPC codes in practical LS-MIMO systems. It is worth noting that the previous analytical tools that have been used to evaluate the performance of P-LDPC codes do not account for the quantization noise effect of the low-resolution ADCs and the fact that the covariance of quantization noise depends on the fading channels. This article addresses this shortcoming by first leveraging the additive quantization noise model. We then derive the expression of extrinsic information for the belief-propagation LS-MIMO detector. The mutual information functions, which are the core elements of our proposed protograph extrinsic information transfer (PEXIT) algorithm, are analyzed for LS-MIMO communication systems. Our proposed PEXIT algorithm allows us to analyze and predict the impact of the low-resolution ADCs on the performance of P-LDPC codes, considering various input parameters, including the LS-MIMO configuration, the code rate, and the maximum number of decoding iterations, and the code structure. Based on our extensive analytical and simulation results, we found that the performance of 3-bit and 4-bit ADC systems only have a small gap to that of the unquantized systems. Especially when the 5-bit ADC scheme is applied, the performance loss is negligible. This finding sheds light on the practical design of LS-MIMO systems using P-LDPC codes.INDEX TERMS Protograph LDPC codes, large-scale MIMO, joint detection and decoding, PEXIT algorithm, low-resolution ADC.

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Section: ) Mutual Information I α [N M]mentioning

confidence: 81%

Section: ) Mutual Information Flow From Variable Nodes To Check Nodesmentioning

confidence: 99%

Performance Analysis of Protograph LDPC Codes Over Large-Scale MIMO Channels With Low-Resolution ADCs

Nguyen¹,

Vu²,

Nguyen

et al. 2019

IEEE Access

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“…The number of major connections will not become so large with high number of antenna elements. Therefore, the effective number of loops with high impact is a few which suits the detection in massive MIMO systems to achieve low complexity [118]. The transmitted signals are detected at each observation node and the result is passed as a message (extrinsic information) to each symbol node.…”

Section: Detectors Based On Belief Propagationmentioning

confidence: 99%

“…In [126], the extrinsic information transfer (EXIT) of a factor graph based on a message passing algorithm has been utilized for a detection in 16 × 16, 64 × 64 and 256 × 256 MIMO systems. A detector based on the EXIT and the BP has been implemented in [118] using 100 × 100 MIMO system. Another detector based on the BP has been implemented using an antenna array of 100 elements with second-order calculations [98].…”

Section: Detectors Based On Belief Propagationmentioning

confidence: 99%

Massive MIMO Detection Techniques: A Survey

Albreem

Juntti

Shahabuddin

2019

IEEE Commun. Surv. Tutorials

347

229

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“…2011 Som et al[80] It is demonstrated that the use of MRF-BP and FG-BP detectors in LS-MIMO-ISI (inter-symbol interference) channels results in almost optimal performance with low complexity. In addition, it is shown that the performance tends to improve with the increase of the number of antennas, which favors the application in LS-MIMO scenarios.2013Abiko et al[107] It is considered the extrinsic information transfer (EXIT) analysis for validation and convergence of iterative detection using BP in LS-MIMO scenarios. The results indicate that there is convergence of performance of the BP detector when the number of antennas is equal to 100.2014Wu et al[108] It is proposed algorithms based on MP iterative approximation using Gaussian approximation, expectation propagation, first order approximation, which demonstrate acceptable performance versus computational complexity relation.…”

mentioning

confidence: 99%

Performance, efficiency and complexity in multiple access large-scale MIMO Systems.

Mussi¹

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First, I would like to thank God for giving me health and opportunity to develop this work. I express my gratitude to my advisor, Prof. Taufik Abrão, for his continuous willingness to meet the demands of this work, sharing his knowledge and experience. His guidance in this process has given me professional and personal growth. I would like to thank my family for the love and encouragement always dedicated to me: my parents Jorge and Nair, my girlfriend Marcela and my sister Tatiana. Last but not least, I thank my friends and colleagues at the State University of Londrina for their support throughout this work: Ricardo, Edno, Álvaro, José Carlos and Aislan; besides Jair and Luiz by the partnership.

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An EXIT Chart Analysis for Belief-Propagation Based Detection in a Large-Scale MIMO System

Cited by 5 publications

References 6 publications

Performance Analysis of Protograph LDPC Codes Over Large-Scale MIMO Channels With Low-Resolution ADCs

Performance Analysis of Protograph LDPC Codes Over Large-Scale MIMO Channels With Low-Resolution ADCs

Massive MIMO Detection Techniques: A Survey

Performance, efficiency and complexity in multiple access large-scale MIMO Systems.

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