Recent Research on Massive MIMO Propagation Channels: A Survey

Zhang, Ping; Chen, Jianqiao; Yang, Xiaoli; Ma, Nan; Zhi, Zhang

doi:10.1109/mcom.2018.1800196

Cited by 60 publications

(36 citation statements)

References 14 publications

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“…Massive MIMO has become a hot research topic in last few years, and, hence, several survey papers related to massive MIMO systems have been published [11], [12], [13], [14], [15], [16]. While these papers review a number of key topics of massive MIMO, none of them extensively discuss the detection techniques.…”

Section: A Relevant Prior Artmentioning

confidence: 99%

“…However, the holistic performance and evaluation of mmWave massive MIMO techniques in real-life scenarios and applications remains an open issue. In [14], an extensive investigation of massive MIMO propagation channels is presented and key differences from the conventional MIMO are discussed. It also reviewed the channel characteristics, measurements and models.…”

Section: A Relevant Prior Artmentioning

confidence: 99%

“…where n = 1, 2, • • • , and ω represents the relaxation parameter that plays a crucial role in the convergence rate. The GS method is a special case of the SOR method [76] where we can obtain (14) from (15) by setting ω = 1. For uplink massive MIMO systems, the signal detection technique using the SOR method is convergent when the relaxation parameter ω satisfies 0 < ω < 2 [77].…”

Section: A Linear Detectors Based On the Approximate Matrix Inversionmentioning

confidence: 99%

See 2 more Smart Citations

Massive MIMO Detection Techniques: A Survey

Albreem

Juntti

Shahabuddin

2019

IEEE Commun. Surv. Tutorials

366

229

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Section: A Relevant Prior Artmentioning

confidence: 99%

Section: A Relevant Prior Artmentioning

confidence: 99%

Section: A Linear Detectors Based On the Approximate Matrix Inversionmentioning

confidence: 99%

See 1 more Smart Citation

Massive MIMO Detection Techniques: A Survey

Albreem

Juntti

Shahabuddin

2019

IEEE Commun. Surv. Tutorials

366

229

View full text Add to dashboard Cite

“…is the self-perturbation term. The elements in K (M ) ∈ C K ×K are the random variables with zero mean and variance 1 M . The EVD of self-perturbation is given as…”

Section: ) Self-perturbation Analysismentioning

confidence: 99%

“…Massive multiple-input multiple-output (MIMO) has been viewed as one of the key technologies to boost the system performance in 5G [1]. In the massive MIMO system, a large number of antennas, e.g., even hundreds of antennas, are used to support the high gain beamforming and spatial multiplexing on a large scale.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Semi-Blind Channel Estimation in Multiuser Massive MIMO Systems With Perturbations

Wang

Song

2019

IEEE Access

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In the massive multiple-input multiple-output (MIMO) systems, pilot contamination and signal perturbation are two important issues in the semi-blind channel estimation methods. To evaluate the effects of pilot contamination and signal perturbation, the covariance matrix of the received signal should be obtained. In specific, the eigenvectors associated with the K largest eigenvalues of the ideal covariance matrix, contain the subspace information of the desired signals, in which the interference and partial noise are eliminated because of asymptotic orthogonality of the fading matrix. Since it is quite difficult to acquire the ideal covariance matrix, the sample covariance matrix calculated by the finite data samples is adopted to approximate the ideal covariance matrix in practice. However, the gap between the ideal covariance matrix and the sample covariance matrix leads to signal perturbation. In this paper, the perturbation analysis of a semi-blind channel estimation in the massive MIMO systems is presented. Simulation results verify the validity of our perturbation analysis. Furthermore, it is demonstrated by simulations that signal perturbation affects system performance by reshaping the eigenvectors and eigenvalue distributions of the target cell and interfering cells. INDEX TERMS Massive MIMO, pilot contamination, semi-blind channel estimation, signal perturbation.

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Radio Reception

Zvonar

2024

Encyclopedia of RF and Microwave Engineering

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Multiple factors influence the radio system performance, including radio propagation, radio link design, radio receiver design, and radio network design. The focus of this section is on the key elements of the radio reception that are starting point for the radio system design. Radio propagation addresses fundamentals of path loss prediction models, outdoor and indoor prediction models, and effects of environment and small‐scale variations resulting in multipath fading. The emphasis is on channel characterization and statistical propagation models. Radio link design part covers link budget and frequency planning. Section on man‐made noise and interference completes the list of external factors that influence radio performance. The aspects of radio receiver design include introduction to radio front‐end parameters, diversity techniques, modulation and coding, and interference suppression techniques.

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Recent Research on Massive MIMO Propagation Channels: A Survey

Cited by 60 publications

References 14 publications

Massive MIMO Detection Techniques: A Survey

Massive MIMO Detection Techniques: A Survey

Analysis of Semi-Blind Channel Estimation in Multiuser Massive MIMO Systems With Perturbations

Radio Reception

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