Future mobile communication systems include millimeter wave (mmWave) frequency bands and high mobility scenarios. To learn how wave propagation and scattering effects change from classical sub 6 GHz to mmWave frequencies, measurements in both bands have to be conducted. We perform wireless channel measurements at 2.55 GHz and 25.5 GHz center frequency at velocites of 40 km/h and 100 km/h. To ensure a fair comparison between these two frequency bands, we perform repeatable measurements in a controlled environment.


Synthetic Digitally Modulated Signal Datasets for Automatic Modulation Classification contain CSPB.ML.2018 and CSPB.ML.2022, two high-quality communication signal datasets with eight modulation types: BPSK, QPSK, 8-PSK, pi/4-DQPSK, MSK, 16-QAM, 64-QAM, and 256-QAM. There are 14,000 signals of each modulation type in each dataset for a total of 112,000 signals per dataset. The two datasets are useful for signal processing testing, neural network (NN) training, initial NN testing, and out-of-distribution NN testing as signal generation parameters differ between the two datasets.


This dataset is related to a method for molecular communication in fluids described on "Fluorescent nanoparticles for reliable communication among implantable medical devices," Carbon, vol. 190, pp. 262-275, Apr. 2022, by Federico Calì, Luca Fichera, Giuseppe Trusso Sfrazzetto, Giuseppe Nicotra, Gianfranco Sfuncia, Elena Bruno, Luca Lanzanò, Ignazio Barbagallo, Giovanni Li-Destri, Nunzio Tuccitto; doi: 10.1016/J.CARBON.2022.01.016. 


The integration of communication and artificial intelligence has become a development trend, one of the applications is semantic communication, but the current research lacks the support of comprehensive datasets. To solve this problem, we built a new image and video dataset, named SCO dataset, for the researches on semantic communication and computing. First, we introduce the peculiarities of the dataset, which contains 5100 images and 138 video clips. Secondly, we we give the data generation and processing methods of the dataset, including images and videos.


The dataset is intended to cover core issues pertaining to the area of a traffic optimization via RET motors inside the antenna on the mobile base station system (BSS). The principle of RET operation was already known to scientists; however, the use of a machine learning and big data provides the possibility of creation an autonomous system, which control RET system.

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Sun, 10/23/2022 - 08:50

The dataset includes processed sequences of optical time domain reflectometry (OTDR) traces incorporating different types of fiber faults namely fiber cut, fiber eavesdropping (fiber tapping), dirty connector and bad splice. The dataset can be used for developping ML-based approaches for optical fiber fault detection, localization, idenification, and characterization. 


GaN-based light emitting diodes (LEDs) are the ideal light sources for visible light communication (VLC). However, both the low modulation bandwidth (MB) and unstable lighting output power (LOP) of LEDs at high current density that restrict the further development of VLC. In this work, micro-LEDs (μLEDs) with embedded N electrodes have been proposed, possessing high MB and remarkable stability.


In this paper, we develop a hierarchical aerial computing framework composed of high altitude platform (HAP) and unmanned aerial vehicles (UAVs) to compute the fully offloaded tasks of terrestrial mobile users which are connected through an uplink non-orthogonal multiple access (UL-NOMA).


This dataset contains pathloss and ToA radio maps generated by the ray-tracing software WinProp from Altair. The dataset allows to develop and test the accuracies of pathloss radio map estimation methods and localization algorithms based on RSS or ToA in realistic urban scenarios. More details on the datasets can be found in the dataset paper:


More than 85% of traffic utilization via mobile phones are consumed in the urban area, and most of the traffic is used for downloading. Improving the throughput in LTE for 1 user equipment (UE) in cities is an urgent problem. The collected data is intended to study a dependence of the KPI mobile base station and neighboring from installation extra technology. This study will support the development of methods for comparing traffic utilization of urban area and carry out recommendations for the Channel Quality Indicator (CQI) increases.