RESUMEN
The focus of most research nowadays in the field of communication technology is on increasing bandwidth in wireless connectivity. Adaptive modulation can be used to enhance efficiency of communication systems. Adaptive modulation requires modulation format identification (MFI) at the receiver side to avoid the overhead required to determine the modulation type at the receiver. We present an MFI algorithm based on fan-beam projection to generate patterns from the constellation diagrams that are more discriminative. The constellation diagrams are obtained as images for eight different modulation formats (2/4/8/16 - PSK and 8/16/32/64 - QAM). Different classifiers such as AlexNet, VGG16, and VGG19 are studied and compared for the task of MFI. Evaluation of this proposed algorithm is performed by estimating the classification accuracy at different optical signal-to-noise ratios (OSNRs) ranging from 5 to 30 dB. The simulation results reveal that the proposed algorithm succeeds in identifying the wireless optical modulation format blindly with a classification accuracy up to 100% even at low OSNR values less than 8 dB compared with the related work.
RESUMEN
Optical wireless communication (OWC) technology is one of several alternative technologies for addressing the radio frequency limitations for applications in both indoor and outdoor architectures. Indoor optical wireless systems suffer from noise and intersymbol interference (ISI). These degradations are produced by the wireless channel multipath effect, which causes data rate limitation and hence overall system performance degradation. On the other hand, outdoor OWC suffers from several physical impairments that affect transmission quality. Channel coding can play a vital role in the performance enhancement of OWC systems to ensure that data transmission is robust against channel impairments. In this paper, an efficient framework for OWC in developing African countries is introduced. It is suitable for OWC in both indoor and outdoor environments. The outdoor scenario will be suitable to wild areas in Africa. A detailed study of the system stages is presented to guarantee the suitable modulation, coding, equalization, and quality assessment scenarios for the OWC process, especially for tasks such as image and video communication. Hamming and low-density parity check coding techniques are utilized with an asymmetrically clipped DC-offset optical orthogonal frequency-division multiplexing (ADO-OFDM) scenario. The performance versus the complexity of both utilized techniques for channel coding is studied, and both coding techniques are compared at different coding rates. Another task studied in this paper is how to perform efficient adaptive channel estimation and hence equalization on the OWC systems to combat the effect of ISI. The proposed schemes for this task are based on the adaptive recursive least-squares (RLS) and the adaptive least mean squares (LMS) algorithms with activity detection guidance and tap decoupling techniques at the receiver side. These adaptive channel estimators are compared with the adaptive estimators based on the standard LMS and RLS algorithms. Moreover, this paper presents a new scenario for quality assessment of optical communication systems based on the regular transmission of images over the system and quality evaluation of these images at the receiver based on a trained convolutional neural network. The proposed OWC framework is very useful for developing countries in Africa due to its simplicity of implementation with high performance.
RESUMEN
In nuclear applications related to radiation energy measurement, digital pulse processing for fast sampling facility has great advantages compared to the traditional analog pulse processing. A distortion in energy spectrum and degradation in timing resolution take place when pulse pile-up occurs. This in turn leads to degradations of the signals used in applications such as nuclear medicine. Pile-up pulses are commonly removed in most algorithms if they are detected, but in this case, getting a clean spectrum becomes a challenge due to data loss. A proposed pile-up detection and recovery algorithm based on fitting the preamplifier data and signal extrapolation is presented. The extrapolated pulse is used for recovering (extracting) the piled-up pulse to estimate its parameters. A smoothed first derivative algorithm is used for peak tracking inside the detected events. To evaluate the proposed pile-up recovery algorithm theoretically and experimentally, it is applied on both simulated input signals generated with different time displacements between the piled-up events, and experimental preamplifier radiation signals. The obtained results prove that the proposed algorithm achieves better utilization of power and can be used for high count rate (high activity elements) spectroscopy systems.
RESUMEN
One of the most important applications of radioisotopes in industry is the residence time distribution (RTD) measurement. RTD can be used for optimizing the design of industrial systems and determining their malfunctions. The RTD signal may be subject to different sorts of noise. This leads to errors in the RTD calculations, and hence leads to wrong analysis in the determination of system malfunctions. This paper presents a proposed approach for RTD signal identification based on power density spectrum (PDS). The cepstral features are extracted from the signal or/and its PDS. The PDS is estimated using nonparametric, parametric, and eigen-analysis methods. The identification results are analyzed and compared for different estimation methods in order to select the best PDS estimation method for RTD signal identification. Neural networks are used for training and testing in the proposed approach. The proposed approach is tested using RTD signals obtained from the measurements carried out with radiotracer technique. The experimental results show that the proposed approach with features extracted from the PDS of the RTD signals calculated using eigen-analysis methods is the most robust and reliable in RTD signal identification.
RESUMEN
This paper presents three laboratory experiments, which have been carried out using the Molybdenum-99 (Mo(99)) radiotracer to measure the residence time distribution (RTD), the mixing time and the flow rate in a water flow rig. The results of the RTD measurement experiment are preprocessed using the MATLAB software for background correction, radioactive decay correction, starting point correction, filtering, and data extrapolation. After preprocessing, six mathematical models are investigated on this data using the International Atomic Energy Agency (IAEA) RTD software. The parameters of each model are optimized to calculate the value of the RTD, and to determine the model, which gives the best match with the practical data. The selected model with the best match is used to calculate the RTD in this experiment. The mixing time experiment is carried out for different rotation speeds and repeated three times in each case. The results show that the mixing time is inversely proportional to the rotation speed. The flow rate experiment is carried out to measure the flow rate in the flow rig. The experimental results show a high reliability of the radiotracer used in the RTD, mixing time and flow rate measurements.