Telecommunications
Afshin Koliji; Sara Mihandoost; Nematollah Ezzati; Ehsan Mostafapour
Abstract
Sudden Cardiac Death (SCD) leads to the killing of millions of people worldwide every year. In this article, sudden cardiac death is predicted by utilizing electrocardiogram signal processing. For this purpose, after extracting the signal of heart rate variations from the electrocardiogram signal, temporal ...
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Sudden Cardiac Death (SCD) leads to the killing of millions of people worldwide every year. In this article, sudden cardiac death is predicted by utilizing electrocardiogram signal processing. For this purpose, after extracting the signal of heart rate variations from the electrocardiogram signal, temporal and non-linear features have been extracted. In the next step, by applying LDA to the combined feature vector, the feature dimensions are reduced and finally, healthy people and high-risk people are classified through Hybrid-RBF classifiers. The obtained results show that there are features in the signal of heart rate variations related to risk-taking individuals near the occurrence of sudden cardiac death, that completely distinguish them from healthy persons. It has also been shown that from 6 minutes before the occurrence of cardiac death, this increase in the probability of risk is quite evident, so that as we get closer to the occurrence of the accident, the probability of its occurrence also increases, and this is enough time to adopt strategies to prevent it. The simulation results achieved by the data available in the MIT-BIH database prove the ability of the presented methods to achieve accurate diagnosis.
Telecommunications
Tamirat Yenealem; Robel Getachew
Abstract
Path loss models estimate the average path loss a signal experiences at a particular distance from a transmitter. However, each type of existing path loss propagation model is designed to predict path loss in a particular environment that may be inaccurate in other different; hence selecting the best ...
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Path loss models estimate the average path loss a signal experiences at a particular distance from a transmitter. However, each type of existing path loss propagation model is designed to predict path loss in a particular environment that may be inaccurate in other different; hence selecting the best path loss model and optimizing it will minimize that inaccuracy. This work presents a comparative analysis of five empirical path loss models, COST- 231, ECC-33, Hata, SUI, and Ericsson model, with respect to the measured data from the 14 selected sites in Hawassa city, Ethiopia at 1800 MHz frequency bands. A drive test methodology was adopted for data collection and Nemo Handy and Nemo Outdoor were used as measuring tools for the test. Error measuring tools such as root mean square error, mean absolute error, standard deviation, and mean absolute percentage error were used to select the terrain type of each site and the path loss model that best fits that site. The results show that not only Hawassa city consists of urban and sub-urban terrains but also ECC-33 and Hata are better estimators for Hawassa urban and sub-urban areas with RMSE of 4.18 and 7.86 respectively. The model tuning using the least square method reduced the RMSE of ECC-33 and Hata to 2.46 and 5.18 respectively. The reduction in RMSE shows that the tuned versions are close to the environment. Hence, using the tuned versions of the selected models will result in good cellular network design and enhance the service quality.
Telecommunications
Fateme Amjadipour; Maryam Imani; Hassan Ghassemian
Abstract
SAR images are used in many applications such as building detection. Extracting the building is very challenging due to the radar nature of the SAR images. However, due to the advantages of radar images such as day and night imaging, building extraction from SAR images is a hot topic. In this context, ...
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SAR images are used in many applications such as building detection. Extracting the building is very challenging due to the radar nature of the SAR images. However, due to the advantages of radar images such as day and night imaging, building extraction from SAR images is a hot topic. In this context, one of the main challenges is the effect of building orientation on the profile created in the SAR image. Also, the two geometric distortions of shadow and layover affect the SAR image. In most building extraction methods, shadow and double bounce are used as two main parameters in building detection. In this paper, different morphological profiles for detecting shadow index and double-bounce index (DMPSIDI) method have been developed using its combination with the method based on statistical features for building extraction. The DMPSIDI method is a morphological-based method that extracts buildings from SAR images independent of changing their profile. The proposed method is also robust to different data using weighting in the main parameters of shadow and double bounce.
Telecommunications
Mehdi Basiri Abarghouei; Reza Saadat
Abstract
This paper proposes a new relaying protocol for transmitting from a cellular user to the base station with the joint cooperation of a Full-Duplex (FD)-enabled Device-to-Device (D2D) pair. In the proposed scheme, the receiver of the D2D acts as a relay, with the cooperation of its transmitter pair via ...
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This paper proposes a new relaying protocol for transmitting from a cellular user to the base station with the joint cooperation of a Full-Duplex (FD)-enabled Device-to-Device (D2D) pair. In the proposed scheme, the receiver of the D2D acts as a relay, with the cooperation of its transmitter pair via D2D communication between them. The cooperation approach of the D2D receiver is chosen as Adaptive Decode-and-Forward (ADF), while the cooperation strategy of the D2D transmitter is chosen as either ADF, Amplify-and-Forward (AF), or Hybrid relaying protocol. These scenarios are named "Decode and Joint Cooperation," "Amplify and Joint Cooperation," and "Hybrid and Adaptive Joint Cooperation," respectively. The Average Symbol Error Probability (ASEP) of the system is studied over independent and identically distributed (i.i.d) complex Gaussian (Rayleigh envelope) channels, with perfect Channel State Information (CSI) in the presence of Residual Self-Interference (RSI) at the FD relays, as well as Co-Channel Interference (CCI). Moreover, closed-form and high Signal-to-Interference-plus-Noise Ratio (SINR) tight ASEP approximations are established. The optimum power allocation is formulated based on the approximate relations, and the optimal solutions and their characteristics are discussed in detail. Analytical comparisons and simulations confirm the theoretical results and demonstrate significant performance improvements.
Telecommunications
Amir Hatamian; Farzad Farshidi; Changiz Ghobadi; Javad Nourinia; Ehsan Mostafapour
Abstract
The increasing risk of cardiovascular diseases, stress, high blood pressure, obesity, sleep disorders, and depression causes electrocardiogram (ECG) monitors to be used for diagnosing health. The main objective of this research is to enhance the quality of the ECG signal using wavelet transform and adaptive ...
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The increasing risk of cardiovascular diseases, stress, high blood pressure, obesity, sleep disorders, and depression causes electrocardiogram (ECG) monitors to be used for diagnosing health. The main objective of this research is to enhance the quality of the ECG signal using wavelet transform and adaptive filters. This research has been made as descriptive-analytic and the method is used in the signal processing stages to calculate the ECG modulation spectrum, the spectral-modulation filtering scheme, and the ECG database from the standard algorithm and performance criteria. The results of the simulation indicate that the conversion of Sym4 and the adaptive filter with the size of 0.0005 and the length of the filter of 25 signals to the noise will be greatly improved to reveal the main features of the ECG signal.
Telecommunications
Ali Eshkevari; Seyed Mohammad Sajad Sadough
Abstract
Direct Position Determination (DPD) is known as an optimal, single-step technique for localizing co-channel signal sources since it processes the data gathered from all the array receiver elements together. In contrast, the commonly used radio location techniques include two independent stages. First, ...
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Direct Position Determination (DPD) is known as an optimal, single-step technique for localizing co-channel signal sources since it processes the data gathered from all the array receiver elements together. In contrast, the commonly used radio location techniques include two independent stages. First, they estimate some initial parameters like direction, time, time-difference, frequency of arrival, etc., or their combination, and second, they localize signal sources using the triangulation of loci generated by the first stage. This disjoint structure leads to the sub-optimality of conventional localization algorithms. In this paper, we compare the Location root-mean-square-Error Lower Bounds (LELB) for DPD and position finding by DOA (PF-DOA) to prove the superiority of DPD over PF-DOA, which are commonly used for tactical fields or outdoor applications. Moreover, we demonstrate the advantages of DPD for indoor localization applications compared to PF-DOA techniques in terms of localization accuracy. We also introduce the single-group-array (SGA) structure for DPD in indoor applications and reveal that it outperforms both the PF-DOA and DPD with a classical multi-group-array (MGA) structure.