Underwater wireless communications refer to data transmission in unguided water environment through wireless carriers, i.e., radio-frequency (RF) wave, acoustic wave, and optical wave. In comparison ...to RF and acoustic counterparts, underwater optical wireless communication (UOWC) can provide a much higher transmission bandwidth and much higher data rate. Therefore, we focus, in this paper, on the UOWC that employs optical wave as the transmission carrier. In recent years, many potential applications of UOWC systems have been proposed for environmental monitoring, offshore exploration, disaster precaution, and military operations. However, UOWC systems also suffer from severe absorption and scattering introduced by underwater channels. In order to overcome these technical barriers, several new system design approaches, which are different from the conventional terrestrial free-space optical communication, have been explored in recent years. We provide a comprehensive and exhaustive survey of the state-of-the-art UOWC research in three aspects: 1) channel characterization; 2) modulation; and 3) coding techniques, together with the practical implementations of UOWC.
In underwater wireless optical communication (UWOC) links, multiple scattering may cause temporal spread of beam pulse characterized by the impulse response, which therefore results in inter-symbol ...interference (ISI) and degrades system error performance. The impulse response of UWOC links has been investigated both theoretically and experimentally by researchers but has not been derived in simple closed-form to the best of our knowledge. In this paper, we analyze the optical characteristics of seawater and present a closed-form expression of double Gamma functions to model the channel impulse response. The double Gamma functions model fits well with Monte Carlo simulation results in turbid seawater such as coastal and harbor water. The bit-error-rate (BER) and channel bandwidth are further evaluated based on this model for various link ranges. Numerical results suggest that the temporal pulse spread strongly degrades the BER performance for high data rate UWOC systems with on-off keying (OOK) modulation and limits the channel bandwidth in turbid underwater environments. The zero-forcing (ZF) equalization designed based on our channel model has been adopted to overcome ISI and improve the system performance. It is plausible and convenient to utilize this impulse response model for performance analysis and system design of UWOC systems.
In underwater wireless optical communications (UWOC), absorption and scattering characterize the link properties since photons may suffer these two processes with energy loss and direction change, ...respectively, when interacting with water molecules or suspended particles. In this work, we consider the effects of absorption and scattering on the probability distribution, i.e., normalized intensity distribution, of photons in space and time domains. Our prior work proposed a stochastic channel model to represent the spatial-temporal probability distribution of propagated photons only for nonscattering and single scattering components of UWOC links. However, multiple scattering will dominate the scattering behavior of the underwater environment with long communication distance and/or more turbid water type. In this work, we take into account all three types of components including nonscattering, single and multiple scattering, and present a more general stochastic channel model which fits well with Monte Carlo simulations in turbid water environment such as coastal and harbor water. Based on the proposed channel model, we also evaluate the performance of path loss, scattering richness, and attenuation of UWOC links. Numerical results suggest that multiple scattering can compensate the path loss overestimated by traditional approaches. Furthermore, scattering richness and attenuation tend to increase but have opposite effects to raise and reduce the received probabilities of higher order scattered photons, respectively, as link range increases.
A swarm of unmanned vehicles can provide fine-grained spatial-temporal information acquisition and monitoring in comparison to a single agent, which is beneficial in terms of environment mapping, ...terrain exploration, and target hunting. However, the cooperation of single type of unmanned vehicles may be not qualified for fulfilling complex underwater tasks considering the motion constraints. In this paper, a joint design of the unmanned aerial/surface/underwater vehicle (UAV-USV-UUV) network, also referred to as 3U network, is proposed for cooperative underwater target hunting. We first introduce the advantages of this 3U heterogeneous system in multi-task cooperation and portray its system model. Moreover, we propose an energy-oriented target hunting model by jointly optimizing the UAV's position, the UUV's trajectory as well as their inter-connectivity. Finally, DQN algorithms are conceived to solve the proposed target hunting problem. Simulation results show the proposed scheme is suitable for underwater target hunting with a high success rate considering a trade-off between the system energy consumption and inter-connectivity.
In this article, a novel driving behavior recognition system based on a specific physical model and motion sensory data is developed to promote traffic safety. Based on the theory of rigid body ...kinematics, we build a specific physical model to reveal the data change rule during the vehicle moving process. In this work, we adopt a nine-axis motion sensor including a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, and apply a Kalman filter for noise elimination and an adaptive time window for data extraction. Based on the feature extraction guided by the built physical model, various classifiers are accomplished to recognize different driving behaviors. Leveraging the system, normal driving behaviors (such as accelerating, braking, lane changing and turning with caution) and aggressive driving behaviors (such as accelerating, braking, lane changing and turning with a sudden) can be classified with a high accuracy of 93.25%. Compared with traditional driving behavior recognition methods using machine learning only, the proposed system possesses a solid theoretical basis, performs better and has good prospects.
In this letter, we focus on the relationship among channel capacity, signal-to-noise ratio (SNR), water types, wind speed, and characteristics of transmiter/receiver array such as inter-spacing and ...link range for downlink underwater wireless optical communications (UWOC) multiple-input multiple-output (MIMO) systems. Numerical results suggest that more turbid water, larger link range, and larger inter-spacing may reduce the channel capacity, and meanwhile more turbid water and larger link range can weaken the effects of random slopes and inter-spacing at the expense of larger SNR to balance the channel capacity.
Main conclusion
High-throughput sequencing and yeast one and two-hybrid library screening reveal that
DKGA2ox1
and
miR171f_3
are involved in the regulation of scion dwarfing with ...‘Nan-tong-xiao-fang-shi’ as interstocks.
Diospyros kaki
Thunb. cv. Nan-tong-xiao-fang-shi (‘Nan-tong-xiao-fang-shi’) interstocks play a critical role in the scion dwarfing. However, the understanding of the molecular signaling pathways that regulate the scion dwarfing with ‘Nan-tong-xiao-fang-shi’ as interstocks remain unclear. In this work, the regulatory network in the scion dwarfing with ‘Nan-tong-xiao-fang-shi’ as interstocks was identified. Using a yeast one-hybrid library screening, luciferase activity analysis, luciferase complementation imaging assays and GFP signal detection, a SPL transcription factor named
Diospyros kaki
SPL (DKSPL), potentially functioning as a transcriptional activator of the
Diospyros kaki GA2ox1
(
DKGA2ox1
) gene, was identified as a key stimulating factor in the persimmon growth and development. The DKSPL was found in the nucleus, and might play a role in the transcriptional regulation system. A microRNA named miR171f_3 was identified, which might act as a negative regulator of
Diospyros kaki
SCR (DKSCR) in persimmon. The interactions between DKSCR and seven proteins were experimentally validated with a yeast two-hybrid library screening. Compared to the non-grafted wildtype persimmon, the tissue section of graft union healed well due to the increased expression of cinnamyl-alcohol dehydrogenase. These results indicate that
DKGA2ox1
and
miR171f_3
may co-promote the scion dwarfing by plant hormone signal transduction pathways.
Abstract The accuracy of short‐term photovoltaic (PV) power prediction is crucial for maintaining power system stability and grid scheduling. Here, a short‐term PV power prediction framework is ...proposed considering combined weather similarity day screening, signal decomposition noise reduction and hybrid deep learning to realize PV power prediction. First, a combined meteorological similar day screening model is constructed to screen out historical days similar to the day, which reduces the number of training sets; Second, Synchrosqueezing Wavelet Transform is utilized to eliminate data noise. Third, a Convolution Neural Network‐Gate Recurrent Unit (CNN‐GRU) network is constructed to extract periodic and nonlinear features in the PV power generation data series and to capture the relationship features between PV power generation and meteorological factors to improve the prediction accuracy. Fourth, the Sparrow Search Algorithm is introduced to perform hyper‐parameter optimization of the CNN‐GRU network to accelerate the model convergence and improve the model training efficiency. Finally, this paper conducts simulation experiments and the experimental results show that the prediction method proposed in this paper can effectively improve the prediction accuracy of short‐term PV power compared to the baseline model, and the method proposed in this paper is superior to other conventional methods.
The miniaturization of spectrometer can broaden the application area of spectrometry, which has huge academic and industrial value. Among various miniaturization approaches, filter-based ...miniaturization is a promising implementation by utilizing broadband filters with distinct transmission functions. Mathematically, filter-based spectral reconstruction can be modeled as solving a system of linear equations. In this paper, we propose an algorithm of spectral reconstruction based on sparse optimization and dictionary learning. To verify the feasibility of the reconstruction algorithm, we design and implement a simple prototype of a filter-based miniature spectrometer. The experimental results demonstrate that sparse optimization is well applicable to spectral reconstruction whether the spectra are directly sparse or not. As for the non-directly sparse spectra, their sparsity can be enhanced by dictionary learning. In conclusion, the proposed approach has a bright application prospect in fabricating a practical miniature spectrometer.
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