Proposal for fiber-optic data acquisition system for Baikal-GVD

The first stage of the construction of the Baikal-GVD deep underwater neutrino telescope is planned to be completed in 2024. For the second stage of the detector deployment, a data acquisition system based on fiber-optic technologies has been proposed, which will allow for increased data throughput and more flexible trigger conditions. A dedicated test facility has been built and deployed at the Baikal-GVD site to test the new technological solutions. We present the principles of operation and results of tests of the new data acquisition system.

Statistical Distortion of Supervised Learning Predictions in Optical Microscopy Induced by Image Compression

The growth of data throughput in optical microscopy has triggered the extensive use of supervised learning (SL) models on compressed datasets for automated analysis. Investigating the effects of image compression on SL predictions is therefore pivotal to assess their reliability, especially for clinical use.We quantify the statistical distortions induced by compression through the comparison of predictions on compressed data to the raw predictive uncertainty, numerically estimated from the raw noise statistics measured via sensor calibration. Predictions on cell segmentation parameters are altered by up to 15% and more than 10 standard deviations after 16-to-8 bits pixel depth reduction and 10:1 JPEG compression. JPEG formats with higher compression ratios show significantly larger distortions. Interestingly, a recent metrologically accurate algorithm, offering up to 10:1 compression ratio, provides a prediction spread equivalent to that stemming from raw noise. The method described here allows to set a lower bound to the predictive uncertainty of a SL task and can be generalized to determine the statistical distortions originated from a variety of processing pipelines in AI-assisted fields.

Smart Resource Allocation Scheme for Mimo Microstrip Wireless Communication

In this paper we have proposed a minimum noise shortest path determination scheme considering the amount of delay and energy consumed with respect to each path. An artificial neural network has been employed for classifying the minimum noise shortest path from the source to destination. A simulation work has been carried out with respect to different Signal-to-Noise (SNR) values in a thirty-node network with one Internet node and 100 bits of message length. Also, a comparison has been made between plain Dynamic Source Routing (DSR) and integrating the minimum noise shortest path algorithm with DSR. The simulation results show that with the increase of SNR, noise constraint in the path reduces, and data throughput increases.

HTS FOR RUSSIA

Предлагается к реализации спутник Ku-диапазона с многолучевой структурой и повторным использованием частот, обладающий высокой пропускной способностью, в несколько раз превышающей аналогичный параметр традиционных космических аппаратов (КА). Рассматриваются технические аспекты построения полезной нагрузки и особенности использования КА в сетях связи. We propose for implementation of a Ku-band communication satellite with a multi-beam configuration and frequency reuse technology, having a data throughput, which is several times higher than that of traditional Ku-band satellites. The technical aspects of constructing the payload and specific features of these satellites' application in communication networks are considered.

Data communication for drone-enabled internet of things

<p><span>Internet of things (IoT) is one of the prominent emerged technology of interconnected devices for people convenient and smart services. Recent advancement in this area caused various new challenges especially deployment of infrastructure. In order to fulfill the network requirements, the dynamic and dedicated drone networks have designed as a cost effective and flexible solution. The technologies of IoT and drone are emerged to collect, forward the data for further process. Data communication among drones and IoT infrastructure is new area of research where various different existing protocol are used. However, still this area need attention due to mobility of drones, obstacles and interferences in these networks. This paper proposes a Drone enabled Data Communication for Internet of Things (DDC-IoT) as a data communication solution for IoT networks, data collection centers and drones. The proposed data commination solution is tested in simulation to analyze its performance especially for real time critical applications in terms of data throughput and data delay.</span></p>

Adaptive Modeling of Prediction of Telecommunications Network Throughput Performances in the Domain of Motorway Coverage

The main goal of this paper is to create an adaptive model based on multilayer perceptron (MLP) for prediction of average downlink (DL) data throughput per user and average DL data throughput per cell within an LTE network technology and in a geo-space that includes a segment of the Motorway 9th January with the access roads. The accuracy of model prediction is estimated based on relative error (RE). With multiple trainings and testing of 30 different variants of the MLP model, with different metaparameters the final model was chosen whose average accuracy for the Cell Downlink Average Throughput variable is 89.6% (RE = 0.104), while for the Average User Downlink Throughput variable the average accuracy is 88% (RE = 0.120). If the coefficient of determination is observed, the results showed that the accuracy of the best selected prediction model for the first variable is 1.4% higher than the accuracy of the prediction of the selected model for the second dependent variable. In addition, the results showed that the performance of the MLP model expressed over R2 was significantly better compared to the reference multiple linear regression (MLR) model used.

Wireless Sensor Networks Using Sub-Pixel Optical Camera Communications: Advances in Experimental Channel Evaluation

Optical wireless communications in outdoor scenarios are challenged by uncontrollable atmospheric conditions that impair the channel quality. In this paper, different optical camera communications (OCC) equipment are experimentally studied in the laboratory and the field, and a sub-pixel architecture is raised as a potential solution for outdoor wireless sensor networks (WSN) applications, considering its achievable data throughput, the spatial division of sources, and the ability of cameras to overcome the attenuation caused by different atmospheric conditions such as rain, turbulence and the presence of aerosols. Sub-pixel OCC shows particularly adequate capabilities for some of the WSN applications presented, also in terms of cost-effectiveness and scalability. The novel topology of sub-pixel projection of multiple transmitters over the receiver using small optical devices is presented as a solution using OCC that re-uses camera equipment for communication purposes on top of video-monitoring.

Parallel Computation of CRC-Code on an FPGA Platform for High Data Throughput

With the rapid advancement of radiation hard imaging technology, space-based remote sensing instruments are becoming not only more sophisticated but are also generating substantially more amounts of data for rapid processing. For applications that rely on data transmitted from a planetary probe to a relay spacecraft to Earth, alteration or discontinuity in data over a long transmission distance is likely to happen. Cyclic Redundancy Check (CRC) is one of the most well-known package error check techniques in sensor networks for critical applications. However, serial CRC computation could be a bottleneck of the throughput in such systems. In this work, we design, implement, and validate an efficient hybrid look-up-table and matrix transformation algorithm for high throughput parallel computational unit to speed-up the process of CRC computation using both CPU and Field Programmable Gate Array (FPGA) with comparison of both methods.

Performance Analysis of Data Transmission for Joint Radar and Communication Systems

This paper investigates the problem of data transmission for the joint radar and communication systems (JRCSs). The performance of the JRCS is characterized by data throughput related to the radar echo data (RED) and communication data rate (CDR). Two spectral coexistence schemes are proposed based on the degree of spectrum sharing for radar and communication, i.e., the isolated subfrequency band (ISFB) and mix-used frequency band (MUFB) schemes. Firstly, the signals of radar and communication are operated on the isolated subcarriers, enabling the received signals to be processed independently and bringing the advantage of interference avoidance. Secondly, the signals of radar and communication can be jointly operated on the same subcarriers for the MUFB scheme, which enhances the spectrum efficiency. Unlike the ISFB scheme, the CDR of the MUFB scheme is maximized along with the interference from the radar signal, and meanwhile, the allocated radar power on each subcarrier is derived by maximizing the radar mutual information. Numerical results show that the MUFB scheme significantly improves the performance of data transmission over the ISFB scheme, and a significant performance gain in the data transmission can be achieved, compared to the average power allocation case.