Performance Analysis of 4×4 TDD-SVD-MIMO System in Suburban Field Trial

Ito, Fumito; Fumiki, Uzawa; Sato, Takahiro; Nakagawa, Takayuki; Iai, Naohiko

doi:10.1109/globecom42002.2020.9348151

Cited by 2 publications

(8 citation statements)

References 11 publications

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“…3 was implemented in python and numpy. The channel model was an 11-path one obtained from outdoor experiments [3]. The Kronecker model [20], Eq.…”

Section: Performance Evaluation Of Compensation Methodsmentioning

confidence: 99%

“…SVD-MIMO transmission methods have been researched as next-generation wireless links for mobile-relay broadcast programs [3]- [5], [8]. In particular, a method using modulation schemes with a high modulation order and turbo codes achieved a maximum transmission rate of 180 Mbps and a frequency utilization efficiency of 10 bit/s/Hz in an experimental mobile environment [3].…”

Section: Related Workmentioning

confidence: 99%

“…This paper uses the uplink (UL) transmission that is specified in ARIB STD-B75 [5] and used in [3], [4], [8] as a system model. The system transmits with up to four streams made by 4 × 4 SVD-MIMO and uses ATC to control the power allocation, coding rate, and modulation schemes in accordance with the channel quality.…”

Section: System Modelmentioning

confidence: 99%

See 2 more Smart Citations

Machine Learning-Based Compensation Methods for Weight Matrices of SVD-MIMO

Makino¹,

Nakagawa²,

Iai³

2023

IEICE Trans. Commun.

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This paper proposes and evaluates machine learning (ML)based compensation methods for the transmit (Tx) weight matrices of actual singular value decomposition (SVD)-multiple-input and multiple-output (MIMO) transmissions. These methods train ML models and compensate the Tx weight matrices by using a large amount of training data created from statistical distributions. Moreover, this paper proposes simplified channel metrics based on the channel quality of actual SVD-MIMO transmissions to evaluate compensation performance. The optimal parameters are determined from many ML parameters by using the metrics, and the metrics for this determination are evaluated. Finally, a comprehensive computer simulation shows that the optimal parameters improve performance by up to 7.0 dB compared with the conventional method.

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“…3 was implemented in python and numpy. The channel model was an 11-path one obtained from outdoor experiments [3]. The Kronecker model [20], Eq.…”

Section: Performance Evaluation Of Compensation Methodsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Machine Learning-Based Compensation Methods for Weight Matrices of SVD-MIMO

Makino¹,

Nakagawa²,

Iai³

2023

IEICE Trans. Commun.

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“…Additionally, field experiments were conducted using a prototype. The results demonstrated that both stable and high-speed transmission could be achieved under constraints on the variable range of throughput by R 14) . In addition, an algorithm for automatically switching N mod was proposed for further compatibility between high-speed and stable transmission.…”

Section: Introductionmentioning

confidence: 96%

“…In addition, an algorithm for automatically switching N mod was proposed for further compatibility between high-speed and stable transmission. The algorithm was evaluated by computer simulation by switching settings between N mod =16, 20 15) .…”

Section: Introductionmentioning

confidence: 99%

[Paper] Field Experiment with FPUs for Mobile Relay Programs with Auto-switching of Total Modulation Orders

Makino,

Sato,

Ito

et al. 2023

MTA

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In this paper, we implement an algorithm that automatically switches the total modulation orders in a field pick-up unit (FPU) for mobile live program productions and evaluate its performance through laboratory and field experiments. We are conducting R&D on high-capacity FPUs for mobile live 4K/8K program productions, such as live broadcasting for road racing. Using adaptive transmission control, we aim for stable transmission in poor propagation environments and high-speed transmission in good ones. The switching algorithm is expected to expand the variable range of throughput. We implemented the algorithm in a prototype and evaluated the algorithm's operation through laboratory and field experiments.As a result, it was confirmed that the variable range of throughput, 2.79 times with the conventional method, was expanded to 3.40 times, and the stable transmission area was expanded.

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Performance Analysis of 4×4 TDD-SVD-MIMO System in Suburban Field Trial

Cited by 2 publications

References 11 publications

Machine Learning-Based Compensation Methods for Weight Matrices of SVD-MIMO

Machine Learning-Based Compensation Methods for Weight Matrices of SVD-MIMO

[Paper] Field Experiment with FPUs for Mobile Relay Programs with Auto-switching of Total Modulation Orders

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