Accurate Performance Analysis of Coded Large-Scale Multiuser MIMO Systems with MMSE Receivers

Zhai, Kai; Ma, Zheng; Lei, Xianfu

doi:10.3390/s19132884

Cited by 2 publications

(1 citation statement)

References 23 publications

(36 reference statements)

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“…A minimum mean square error (MMSE) detector was used for channel estimation of massive MIMO systems [8]. In [9], the pairwise error probability (PEP) of the massive multiuser MMSE-MIMO systems was derived. However, the hardware complexity of MIMO also increased.…”

Section: Introductionmentioning

confidence: 99%

Outage Probability Performance Prediction for Mobile Cooperative Communication Networks Based on Artificial Neural Network

Wang

2019

Sensors

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This paper investigates outage probability (OP) performance predictions using transmit antenna selection (TAS) and derives exact closed-form OP expressions for a TAS scheme. It uses Monte-Carlo simulations to evaluate OP performance and verify the analysis. A back-propagation (BP) neural network-based OP performance prediction algorithm is proposed and compared with extreme learning machine (ELM), locally weighted linear regression (LWLR), support vector machine (SVM), and BP neural network methods. The proposed method was found to have higher OP performance prediction results than the other prediction methods.

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Section: Introductionmentioning

confidence: 99%

Outage Probability Performance Prediction for Mobile Cooperative Communication Networks Based on Artificial Neural Network

Wang

2019

Sensors

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A Very Low Complexity QRD-M MIMO Detection Based on Adaptive Search Area

Kim

et al. 2020

Electronics

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We propose a low complexity QR decomposition (QRD)-M multiple input multiple output (MIMO) detection algorithm based on adaptive search area. Unlike the conventional QRD-M MIMO detection algorithm, which determines the next survivor path candidates after searching over the entire constellation points at each detection layer, the proposed algorithm adaptively restricts the search area to the minimal neighboring constellation points of the estimated QRD symbol according to the instantaneous channel condition at each layer. First, we set up an adaptation rule for search area using two observations that inherently reflect the instantaneous channel condition, that is, the diagonal terms of the channel upper triangle matrix after QR decomposition and Euclidean distance between the received symbol vector and temporarily estimated symbol vector by QRD detection. In addition, it is found that the performance of the QRD-M algorithm degrades when the diagonal terms of the channel upper triangle matrix instantaneously decrease. To overcome this problem, the proposed algorithm employs the ratio of each diagonal term and total diagonal terms. Moreover, the proposed algorithm further decreases redundant complexity by considering the location of initial detection symbol in constellation. By doing so, the proposed algorithm effectively achieves performance near to the maximum likelihood detection algorithm, while maintaining the overall average computation complexity much lower than that of the conventional QRD-M systems. Especially, the proposed algorithm achieves reduction of 76% and 26% computational complexity with low signal to noise ratio (SNR) and high SNR, compared with the adaptive QRD-M algorithm based on noise power. Moreover, simulation results show that the proposed algorithm achieves both low complexity and lower symbol error rate compared with the fixed QRD-M algorithms.

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Accurate Performance Analysis of Coded Large-Scale Multiuser MIMO Systems with MMSE Receivers

Cited by 2 publications

References 23 publications

Outage Probability Performance Prediction for Mobile Cooperative Communication Networks Based on Artificial Neural Network

Outage Probability Performance Prediction for Mobile Cooperative Communication Networks Based on Artificial Neural Network

A Very Low Complexity QRD-M MIMO Detection Based on Adaptive Search Area

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