scholarly journals Application of Diversity Combining with RLS Adaptive Filtering in Data Transmission in a Hydroacoustic Channel

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7255
Author(s):  
Agnieszka Czapiewska ◽  
Andrzej Luksza ◽  
Ryszard Studanski ◽  
Andrzej Zak
Keyword(s):  
Least Squares ◽  
Adaptive Filtering ◽  
Data Transmission ◽  
Intersymbol Interference ◽  
Multipath Propagation ◽  
Recursive Least Squares ◽  
Diversity Combining ◽  
Quality Of Data ◽  
Transmission Parameters

When transmitting data in a hydroacoustic channel under difficult propagation conditions, one of the problems is intersymbol interference (ISI) caused mainly by the effect of multipath propagation. This phenomenon leads to a decrease in transmission parameters, and sometimes completely prevents it. Therefore, we have made an attempt to use diversity combining with Recursive Least Squares (RLS) adaptive filtering to improve the quality of data transmission in a hydroacoustic channel with strong reflections. The method was tested in simulation and during measurements in a real environment. The influence of the method on data transmission in the hydroacoustic channel was examined in detail. The obtained results allow us to draw conclusions regarding the purposefulness of use of diversity combining and RLS adaptive filtering in order to improve the quality of data transmission by reducing the effect of ISI.

scholarly journals Reduction of the Multipath Propagation Effect in a Hydroacoustic Channel Using Filtration in Cepstrum

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 751 ◽  
Author(s):  
Agnieszka Czapiewska ◽  
Andrzej Luksza ◽  
Ryszard Studanski ◽  
Andrzej Zak
Keyword(s):  
Data Transmission ◽  
Multipath Propagation ◽  
Propagation Effect ◽  
Quality Of Data ◽  
Multipath Effect ◽  
Channel One ◽  
Real Environment ◽  
Transmission Parameters ◽  
Cepstral Analysis

During data transmission in a hydroacoustic channel, one of the problems is the multipath propagation effect, which leads to a decrease in the transmission parameters and sometimes completely prevents it. Therefore, we have attempted to develop a method, which is based on a recorded hydroacoustic signal, that allows us to recreate the original (generated) signal by eliminating the multipath effect. In our method, we use cepstral analysis to eliminate replicas of the generated signal. The method has been tested in simulation and during measurements in a real environment. Additionally, the influence of the method on data transmission in the hydroacoustic channel was tested. The obtained results confirmed the usefulness of the application of the developed method and improved the quality of data transmission by reducing the multipath propagation effect.

МЕТОД ГЛУБОКОГО ОБУЧЕНИЯ С ПОДКРЕПЛЕНИЕМ ДЛЯ СИСТЕМ ИНТЕРНЕТА ВЕЩЕЙ НА БАЗЕ ТЕХНОЛОГИИ LORA С ОГРАНИЧЕННЫМИ РЕСУРСАМИ И ПОДДЕРЖКОЙ QoS

2021 ◽  
Author(s):  
 M.S. MUTHANNA ◽  
A.S. MUTHANNA ◽  
 A.S. BORODIN
Keyword(s):  
Data Transmission ◽  
Environmental Parameters ◽  
Code Rate ◽  
Frame Structure ◽  
Signal Quality ◽  
High Quality ◽  
Spreading Factor ◽  
Transmission Parameters ◽  
Factor Code

Achieving high Quality of Service (QoS) remains a challenge for LoRa technology. However, high QoS can be achieved via optimizing the transmission policy parameters such as bandwidth and code rate. Existing approaches do not provide an opportunity to optimize the LoRa networks' data transmission parameters. The article proposes transmission policy enforcementfor QoS-aware LoRanetworks.The QoSparameter ranking is implemented for IoT nodes where priority and nonpriority information is identified by the new field of LoRa frame structure(QRank).The optimaltransmissionpolicyenforcement uses fast deep reinforcement learning that utilizes the environmental parameters including QRank, signal quality, and signal-to-interference-plus-noise-ratio. The transmission policy is optimized for spreading factor, code rate, bandwidth, and carrier frequency. Performance evaluation is implemented using an NS3.26 LoRaWAN module. The performance is examined for various metrics such as delay and throughput. Достижение высокого качества обслуживания (QoS) по-прежнему остается достаточно сложной задачей для технологии LoRa. В принципе высокий уровень QoS может быть достигнут за счет оптимизации параметров передачи, например, пропускной способности и скорости передачи информации в сети. Известные на сегодняшний день решения не дают возможности оптимизировать параметры передачи данных для сетей LoRa. В статье предложен эффективный метод передачи данных, обеспечивающий требования по QoS при использовании технологии LoRa. Ранжирование параметров QoS для узлов интернета вещей определяется новым полем структуры фрейма LoRa (QRank) для приоритетной и неприоритетной информации. Для обеспечения эффективной передачи применяется быстрое глубокое обучение с подкреплением, для которого используются как параметры качества обслуживания, так и отношение сигнал/шум. Метод передачи оптимизирован с учетом коэффициента распространения, скорости передачи данных, полосы пропускания и несущей частоты. Оценка производительности при применении предложенного метода проведена с использованием модуля LoRaWAN в пакете имитационного моделирования NS3.26. Производительность оценивается на основе параметров задержки и пропускной способности.

scholarly journals Evoked Hemodynamic Response Estimation to Auditory Stimulus Using Recursive Least Squares Adaptive Filtering with Multidistance Measurement of Near-Infrared Spectroscopy

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Yan Zhang ◽  
Xin Liu ◽  
Dan Liu ◽  
Chunling Yang ◽  
Qisong Wang ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Least Squares ◽  
Auditory Stimulus ◽  
Near Infrared Spectroscopy ◽  
Adaptive Filtering ◽  
Near Infrared ◽  
Continuous Wave ◽  
Hemodynamic Response ◽  
Recursive Least Squares ◽  
Functional Near Infrared Spectroscopy

The performance of functional near-infrared spectroscopy (fNIRS) is sometimes degraded by the interference caused by the physical or the systemic physiological activities. Several interferences presented during fNIRS recordings are mainly induced by cardiac pulse, breathing, and spontaneous physiological low-frequency oscillations. In previous work, we introduced a multidistance measurement to reduce physiological interference based on recursive least squares (RLS) adaptive filtering. Monte Carlo simulations have been implemented to evaluate the performance of RLS adaptive filtering. However, its suitability and performance on human data still remain to be evaluated. Here, we address the issue of how to detect evoked hemodynamic response to auditory stimulus using RLS adaptive filtering method. A multidistance probe based on continuous wave fNIRS is devised to achieve the fNIRS measurement and further study the brain functional activation. This study verifies our previous findings that RLS adaptive filtering is an effective method to suppress global interference and also provides a practical way for real-time detecting brain activity based on multidistance measurement.

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