scholarly journals Towards traffic-oriented spreading factor allocations in LoRaWAN systems

2018 ◽  
Author(s):  
Francesca Cuomo ◽  
Julio Cesar Carrasquel Gamez ◽  
Antonio Maurizio ◽  
Laura Scipione ◽  
Manuel Campo ◽  
...  
Keyword(s):  
Spreading Factor

scholarly journals M-ary nonlinear sine chirp spread spectrum for underwater acoustic communication based on virtual time-reversal mirror method

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Songzuo Liu ◽  
Habib Hussain Zuberi ◽  
Yi Lou ◽  
Muhmmad Bilal Farooq ◽  
Shahabuddin Shaikh ◽  
...  
Keyword(s):  
Acoustic Communication ◽  
Time Reversal ◽  
Spread Spectrum ◽  
Underwater Acoustic Communication ◽  
Half Cycle ◽  
Spreading Factor ◽  
Underwater Acoustic ◽  
Virtual Time ◽  
Chirp Spread Spectrum ◽  
Time Reversal Mirror

AbstractLinear chirp spread spectrum technique is widely used in underwater acoustic communication because of their resilience to high multipath and Doppler shift. Linear frequency modulated signal requires a high spreading factor to nearly reach orthogonality between two pairs of signals. On the other hand, nonlinear chirp spread spectrum signals can provide orthogonality at a low spreading factor. As a result, it improves spectral efficiency and is more insensitive to Doppler spread than the linear counterpart. To achieve a higher data rate, we propose two variants (half cycle sine and full cycle sine) of the M-ary nonlinear sine chirp spread spectrum technique based on virtual time-reversal mirror (VTRM). The proposed scheme uses different frequency bands to transmit chirp, and VTRM is used to improve the bit error rate due to high multipath. Its superior Doppler sensitivity makes it suitable for underwater acoustic communication. Furthermore, the proposed method uses a simple, low-power bank of matched filters; thus, it reduces the overall system complexity. Simulations are performed in different underwater acoustic channels to verify the robustness of the proposed scheme.

scholarly journals Isolation of human serum spreading factor.

1983 ◽  
Vol 258 (20) ◽  
pp. 12548-12552 ◽  
Author(s):  
D W Barnes ◽  
J Silnutzer
Keyword(s):  
Human Serum ◽  
Spreading Factor

Cell density affects spreading and clustering, but not attachment, of human keratinocytes in serum-free medium

1991 ◽  
Vol 99 (2) ◽  
pp. 387-395
Author(s):  
M. Malcovati ◽  
M.L. Tenchini
Keyword(s):  
Cell Density ◽  
Time Course ◽  
Cluster Formation ◽  
Physicochemical Characterization ◽  
Human Keratinocytes ◽  
Conditioned Media ◽  
Serum Free Medium ◽  
Free Medium ◽  
Spreading Factor ◽  
Serum Free

Attachment, spreading and clustering of second-passage human human keratinocytes in serum-free medium have been evaluated within 24 h after plating, as a function of the density of the inoculum and of time, in two different strains. The results show that attachment is unaffected by cell density and differs significantly from strain to strain. Cell density affects the distribution of attached keratinocytes among three morphologically distinct classes: unspread, spread and clustered cells. The percentage of unspread keratinocytes shows a linear decrease at increasing cell density, and that of spread keratinocytes an increase, resulting from statistically significant increases in the percentages of both single and clustered cells. Spreading on uncoated surfaces appears therefore as an inducible phenomenon. The use of media conditioned by keratinocytes, fibroblasts and HeLa cells shows that keratinocytes specifically secrete a diffusible ‘spreading factor’. We term this phenomenon ‘autocrine induced spreading’. Preliminary physicochemical characterization suggests that a protein could be responsible for the spreading activity of conditioned media. The ‘spreading factor’ seems to act directly on the cells, and not through a modification of the plastic surface of the dishes, since most (greater than 70%) of the spreading activity can be recovered in the conditioned media used in pre-coating experiments. The percentages of clusters follow ‘saturation’ kinetics at increasing cell density, while the percentage of clustered cells increases linearly with the density of inoculum. Time-course experiments show that the rate of spreading is cell density- and strain-independent. The percentages of clusters and of total clustered cells are time-independent, suggesting that cluster formation takes place in suspension.(ABSTRACT TRUNCATED AT 250 WORDS)

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.

Anisotropic geometrical-spreading correction for wide-azimuth P-wave reflections

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. D161-D170 ◽  
Author(s):  
Xiaoxia Xu ◽  
Ilya Tsvankin
Keyword(s):  
Transversely Isotropic ◽  
Azimuthal Anisotropy ◽  
P Wave ◽  
Fractured Reservoir ◽  
Geometrical Spreading ◽  
Spreading Factor ◽  
Velocity Anisotropy ◽  
Reflection Data ◽  
Fitting Procedure ◽  
Avo Attributes

Compensation for geometrical spreading along a raypath is one of the key steps in AVO (amplitude-variation-with-offset) analysis, in particular, for wide-azimuth surveys. Here, we propose an efficient methodology to correct long-spread, wide-azimuth reflection data for geometrical spreading in stratified azimuthally anisotropic media. The P-wave geometrical-spreading factor is expressed through the reflection traveltime described by a nonhyperbolic moveout equation that has the same form as in VTI (transversely isotropic with a vertical symmetry axis) media. The adapted VTI equation is parameterized by the normal-moveout (NMO) ellipse and the azimuthally varying anellipticity parameter [Formula: see text]. To estimate the moveout parameters, we apply a 3D nonhyperbolic semblance algorithm of Vasconcelos and Tsvankin that operates simultaneously with traces at all offsets andazimuths. The estimated moveout parameters are used as the input in our geometrical-spreading computation. Numerical tests for models composed of orthorhombic layers with strong, depth-varying velocity anisotropy confirm the high accuracy of our travetime-fitting procedure and, therefore, of the geometrical-spreading correction. Because our algorithm is based entirely on the kinematics of reflection arrivals, it can be incorporated readily into the processing flow of azimuthal AVO analysis. In combination with the nonhyperbolic moveout inversion, we apply our method to wide-azimuth P-wave data collected at the Weyburn field in Canada. The geometrical-spreading factor for the reflection from the top of the fractured reservoir is clearly influenced by azimuthal anisotropy in the overburden, which should cause distortions in the azimuthal AVO attributes. This case study confirms that the azimuthal variation of the geometrical-spreading factor often is comparable to or exceeds that of the reflection coefficient.

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