International Journal of Intelligent Engineering and Systems

1

Authors: Rachapalli Sunanda, Joseph Beatrice Seventline

The rainy effect normally decreases the visual quality of the images that highly affects the outdoor vision system’s performance. Due to light scattering, the rain streaks generate the haziness and blurring effect. So, an effective model is required to remove rain streaks from the single image that assists an extensive range of applications such as object tracking, image enhancement, etc. In this research work, a new model has been proposed for rain streak removal in the single image. In the proposed work, a global sparse model with Singular Value Decomposition (SVD) and Huber loss function were used to remove rain streaks from the synthesized images. In the proposed model, three sparse terms (characteristics of image background information, structural knowledge and intrinsic direction of rain streaks) were used for depicting the directional smoothness of rain-free and rain streak images and also described the intrinsic and latent properties of rain streaks. The rain streaks sparsity was also enhanced by employing l_1 norm that effectively avoids the undesired features on the rain free regions. Then, Alternating Direction Method of Multipliers (ADMM) was used for tackling the proposed model in order to achieve optimal solutions. In the experimental phase, the proposed model was compared with the existing models like Cascading Attention Aggregation Network (CAAN) and Directional Global Sparse Model (DGSM) in terms of Peak Signal to Noise Ratio (PSNR), Structural Similarity (SSIM), and Root Mean Square Error (RMSE). Through the experimental simulation, the proposed model almost showed 0.52-1 dB improvement in PSNR value.

21

Authors: Saha Tanangsanakool, Pongsathorn Reangsuntea, Kazuo Mori, Pisit Boonsrimuang

Orthogonal Frequency Division Multiplexing (OFDM) signal would be damaged significantly by inter-carrier interference (ICI) in higher time-varying fading channels. The ICI leads to fatal degradation of bit error rate (BER) performance due to the loss of orthogonality among subcarriers. To solve this problem, this paper proposes a high accuracy time-domain channel impulse response (CIR) estimation method and low-complexity based time-domain equalization (TDE) method for solving the simultaneous equations instead of using an inverse matrix calculation which can achieve better BER performance and lower computation complexity even in higher time-varying fading channels. The salient features of proposed method are to employ a time-domain training sequence (TS) in the estimation of channel impulse response (CIR) instead of using pilot subcarriers in the frequency domain and to employ the time domain equalization (TDE) method with maximum likelihood (ML) estimation instead of using a conventional frequency domain equalization (FDE) method. This paper also proposes a low-complexity iterative method for solving the simultaneous equations instead of using an inverse matrix calculation, which remains the computation complexity up to 7.8% of inverse matrix calculation with the same BER performance but achieves the BER performance when compared with the conventional method. This paper presents various simulation results in higher time-varying fading channels (vehicle speed ≈ 381 km/hrs) to demonstrate the effectiveness of the proposed method as compared with conventional FDE and TDE methods.

44

Authors: Anny Kartika Sari

Concept mapping between two different ontologies in the biomedical field are commonly conducted. When one of the ontologies changes, the changes should be propagated to the other ontology in the mapping. This propagation process is an issue that must be addressed because the knowledge in biomedical field develops rapidly. In this paper, we present the change propagation method from Gene Ontology (GO) to Medical Subject Headings (MeSH). The change propagation is conducted by mapping GO change operations into MeSH change operations. There are three steps that must be performed. Firstly, the change operations on each ontology are identified and represented formally. Secondly, change operations in both ontologies are classified and compared. Finally, each GO change operation is mapped into a MeSH change operation based on the semantic meaning of the change operation. A proof of concept is also presented to show how the process works. In the experiment, the method has been applied to ten concept deletion operations of GO, with 80% of operations being successfully propagated to MeSH. The 100% success cannot be achieved because some GO concepts do not have relevant corresponding MeSH concepts due to the specificity of GO concepts.

66

Authors: Ali Hayder Abdul Kareem

This paper introduces the concept of designing all optical orthogonal frequency division multiplexing (AO-OFDM) techniques to increase data rates to obtain a greater range of transmission. Arrayed waveguide grating (AWG) was proposed in this work as inverse fast fourier transform / fast fourier transform (IFFT/FFT) circuits in all optical orthogonal frequency division multiplexing system for its structure is simplified and capacity in large subcarriers. AWG combining with dense wave division multiplexing (DWDM) technique with 20 GHz channel spacing. The proposed system is simpler than others, which can obtain AO-OFDM and have efficiency in the spectrum. The output investigated for the proposed system is evaluated by applying different input power and transmission lengths to assess the quality of the signal via the bit error rate (BER) parameter. The simulation results show the constellation diagram and BER of the received signal with 8 channels, using quadrature amplitude modulation (QAM) and quadrature phase shift keying (QPSK) at (240 Gb/s) per channel.

90

Authors: Kamal A. El Dahshan, Eman K. Elsayed, Ashraf Aboshoha, Ebeid A. Ebeid

Classification of human face images into emotion categories is a hard challenge. Deep learning is mostly effective for this task. In this paper, we propose a facial emotions recognition system based on Deep Belief Networks (DBNs) and Quantum Particle Swarm Optimization (QPSO). The proposed methodology is composed of four phases: first, the input image is preprocessed by cropping the Region Of Interest (ROI) in order to get the desired region and discard non-significant parts. Second, the ROI is divided into many blocks and then the integral image is utilized to determine the superior (most efficient) blocks. Third, image down sampling algorithm is adapted to reduce the size of the new sub image in order to improve the system performance. Fourth, the emotion's class is identified using the DBN. Instead of adapting DBN parameters manually, QPSO is used to automatically optimize DBN parameters' values. The proposed algorithm has been applied to the Japanese female facial expression (JAFFE) and FER-2013 datasets. By applying the proposed algorithm, the computation time is reduced effectively by about 62% on the whole JAFFE and 82% on the whole FER-2013 datasets. Whereas, the accuracy is retained at 97.2% and 68.1% on JAFFE and FER-2013 datasets respectively.

114

Authors: Riyadh Toman Thahab, Tahani H. M. Al-Mhana

Furnished with many features, modular multi-level converters (MMC) have various applications in power systems. The main application considered is high voltage direct current transmission (HVDC), where the MMC operates as back to back converters. In this work, an MMC is studied as an interfacing converter, between a distributed energy source and an unbalanced grid. Therefore, at the point of common coupling (PCC) the voltage and current is a composite of positive, negative and zero sequence components. A mathematical relationship for the MMC arm current is developed that accounts for the presence of the PCC voltage and current zero sequence in addition to the positive and negative components. Since current is injected towards the grid, the profile of the converter output voltage is an important factor. This voltage is implicitly affected by the sub-module capacitor voltage; hence, the balancing scheme adopted is pivotal in grid connected applications. Therefore, two balancing techniques are investigated, where one depends on simply rotating the carriers between sub-modules of the MMC. The other is based on the conventional sorting algorithm. Results show that the former method, which requires less calculation efforts, provides sufficient results in-terms of the current shape and ripple injected by the converter compared to the sorting based benchmark scheme. This is attributed to the converter output voltage, for which simulation results confirm that the rotation method contributes to small deviations in this voltage. Evaluations of balancing methods presented in this work prove that the rotation method is a sufficient balancing platform for interfacing MMC applications.

145

Authors: Ayat Taha, Ashraf Darwish, Aboul Ella Hassanien, Ahmed ElKholy

In this paper, the identification system for the Arabian horse based on the biometric features is presented. This system used the Local Binary Pattern (LBP), Speed Up Robust Features (SURF) to extract the biometric features from the muzzle print images of the Arabian horse and to increase the robustness of the features against noise, illumination and rotation a fusion of SURF and LBP is presented to form LS features. The system also used the Support Vector Machine (SVM) classifier to perform the identification and gender determination process using the extracted features. To improve the accuracy of the proposed system Gray Wolf Optimization Algorithm (GWO) is used to optimize the SVM parameter. The experimental results represent that the proposed system achieved a promising accuracy of 96% using LS features without optimization. After Applying the GWO algorithm the accuracy of the system using LS features achieved the best accuracy 99.6% compared to SURF and LBP features.

171

Authors: Khamla NonAlinsavath, Lukito Edi Nugroho, Widyawan Widyawan, Kazuhiko Hamamoto

Location-based service has become an important element in indoor positioning with increasing precision. Indoor technologies help with user navigation and positioning in specific locations. Many location-based services and applications have been developed to improve indoor positioning, especially to deal with the complexity of location awareness systems. This study proposes the use of Wi-Fi Fingerprint (Wi-Fi), pedometer and Bluetooth Low Energy 4.0 (BLE) beacon to measure and pinpoint user’s indoor locations using received signal strength-based indoor localization. The system tracks, directs and guides user’s indoor movements using an android application and assists first-time visitors to find a particular location. The networks are comparable and can be detected using smartphones. The phones will detect the strongest signal from the available networks. Wi-Fi, pedometer and BLE 4.0 beacon were able to identify the direction and location in indoor environments and assist user to find their specific destination easily. The map provided by the system based on position information has an accuracy of 91.5% at the third floor and 97.1 % at the second floor, and the signals have seamlessly worked together in integrated fashion when user is in indoor environment. The system is also able to highlight pathway according to user’s current location and destination, in addition to being fast responding, secure and robust. The application enables seamless service in real-time operation and provides multiple pathways, guidance and highlighted map for indoor localization. The display of distance between the user and the destination as the user near the target destination is an extremely helpful feature in the application.

196

Authors: Nam-Soo Kim

Most of the coordinated multipoint (CoMP) transmission studies have been focused on the sum capacity. However, the increase of the sum capacity does not guarantee the individual user’s required outage performance. In this paper, we consider the outage performance of non-orthogonal multiple access (NOMA) networks with CoMP transmission under multi-cell environments. We adapt the Alamouti code for CoMP transmission to improve the outage performance of a cell-edge user. Also to provide the spatial diversity gain, cell selection with maximum channel gain is adapted. Outage probabilities of users are derived in closed-form and verified through Monte Carlo simulation. It is noticed that the outage performance improves as a near user approaches a base station, however, the error floor which does not improve the performance as the transmit power increases is observed. Since the inter cell interference (ICI) from the selected cell with NOMA causes the error floor, the selected cell with orthogonal multiple access (OMA) shows better outage performance for the near user than the cell with NOMA. Furthermore, the performance is more susceptible to the distance between the base station and the near user rather than power allocation to the user. Also, the performance of the cell-edge user shows significant improvement with the combination of the Alamouti code and the cell selection compared to the cell selection only.

216

Authors: Mohammad Dehghani, Zeinab Montazeri, Shahrzad Saremi, Ali Dehghani, Om Parkash Malik, Kamal Al-Haddad, Josep M. Guerrero

A number of metaphysical algorithms have been developed in recent years. Most of these algorithms are inspired by physical processes or living beings' behaviour. In this paper, a new algorithm namely “Hide Objects Game Optimization (HOGO)” is presented to obtain quasi-optimal solution. It is inspired by an old game and the searcher agents who try to find a hidden object in a given space. In this game, any player must notice the following points: (a) pay attention to the voices made by the coach for players, (b) get closer to the best player for whom the coach made the loudest voice, (c) take influence from the voices made by the coach for other players, (d) compare the new voice after a move with the old voice before the move and return back in case the voice gets lower. HOGO is tested on 23 well-known benchmark test functions and is compared with eight optimization algorithms: Genetic Algorithm, Particle Swarm Optimization, Gravitational Search Algorithm, Teaching Learning Based Optimization, Grey Wolf Optimizer, Grasshopper Optimization Algorithm, Spotted Hyena Optimizer, and Emperor Penguin Optimizer. The results and data obtained from applying HOGO and other said algorithms show that HOGO is able to provide better results in comparison with other well-known optimization algorithms.

237

Authors: Nora Niazy, Ahmed El-Sawy, Mahmoud Gadallah

The capacitated vehicle routing problem is the most popular type of vehicle routing problem and is a kind of NP-hard optimization problems. The purpose of this problem is to decrease the total distance travelled by vehicles with respect to restrictions of vehicles’ capacity. In this paper the capacitated vehicle routing problem solved by Chicken Swarm Optimization algorithm, Tabu Search and a new hybrid algorithm. The main idea of the proposed algorithm is to use the hieratical order of Chicken Swarm Algorithm and Tabu Search for finding best neighbourhood to find shortest path with minimum cost, after that we using the moving equations of the two algorithms on each chicken to construct the paths then we choose the shortest path which has the minimum cost. Results from a computational experiment on 10 different datasets show that the hybrid algorithm can be considered as an efficient approach and overcome the best known results in 9 datasets which means that it is 90% better than known results.

260

Authors: Ari Endang Jayati, Wirawan Wirawan, Titiek Suryani, Endroyono Endroyono

Recently, various application scenarios have emerged in new communication networks that have a variety of new requirements such as: ultra-low latency, low out-of-band emission and long battery life. Generalized Frequency Division Multiplexing (GFDM) is one of the nonorthogonal multicarrier techniques that meets these requirements. We study the analysis of nonlinearity effects in a High Power Amplifier (HPA) and crosstalk on Multiple Input Multiple Output (MIMO)-GFDM systems and its compensation. Moreover, proposed is a recurrent receiver compensation method for the joint RF interference in the MIMO-GFDM system. The assumptions made at the receiver considered the characteristics of the HPA. This proposed technique also has the ability to compensate for the combined effects of nonlinear and crosstalk distortion. The simulation results show an improvement in the bit error rate for small iteration numbers, i. e. 1 - 4 iterations for 16-OQAM mapping. The receiver-based mitigation techniques were used as an option to maintain low-level transmitter complexity. The main advantage is the possible application at the base station without increasing the computational complexity of the mobile terminal as well as the terminal costs or battery life. This means the advanced nature of the technique ensured there was no need to make any changes on the cellular terminal side. Therefore, the performance of the iterative receiver technique proposed in the MIMO-GFDM system is better than other orthogonal multicarrier systems.

283

Authors: Dhafer R. Zaghar, Hadeel N. Abdullah, Ikhlas M. Farhan

This paper investigates the application of advanced forward error correction techniques mainly: Raptor code, Low-Density Parity Checks (LDPC) code, and Luby Transform (LT) for wireless communication systems in the low power regime (LPR). Raptor codes are a significant theoretical and practical improvement over LT codes, which were the first actual class of fountain codes. These codes are under consideration for many recent technologies. Different code parameters such as code rate and several decoding iterations are used to show their effect on the performance of digital systems. In this paper, we propose a systematic Raptor code that enabled transmission of information with different code rates in LPR. Simulation results showed that the suggested design is appropriate for data transmission in a low SNR regime and can provide a reasonable bit error rate (BER) against the additive white Gaussian noise(AWGN) with the optimum selection rate1/4 and 1/9. A more significant improvement in the system's BER performance for the SNR up to -5dB over binary input additive white Gaussian noise (BI-AWGN) channels that showed through simulation results. Also, the BPSK modulation with systematic Raptor code is performed better than QPSK modulation in a limited power region, for the same coding rate and the number of decoding iterations.

305

Authors: Yulindon Yulindon, Noor Azah Samsudin, Riswan Efendi

The antenna simulation is generally done manually where certain antenna parameters are changed by trial and error method until the desired performance is obtained. In this study, the E-shaped microstrip antenna was designed to work in wideband frequency using the Particle Swarm Optimization (PSO) algorithm. The E-shaped patch antenna with ground follows the subtraction size. The type of substrate used in this study is FR4 Epoxy with a relative dielectric constant value (r) = 4.6 and thickness (h) = 1.6 mm. Feeding technique used in the connector is a probe feed technique to get matching impedance that matches the impedance of the connector which is 50 ohms. The working frequency of the E-shaped microstrip antenna after the use of the PSO algorithm generated bandwidth of 295 MHz with a working frequency of 340-635 MHz. From several stages of optimization performed, an ideal gain is obtained in accordance with the characteristics of the E-shaped antenna, where the resulting gain is 3.246 dBi. The characteristic obtained is omnidirectional, where the donut-shaped radiation pattern with the direction of the wave is in all directions.

333

Authors: Sujatha Arun Kokatnoor, Balachandran Krishnan

Online ratings and customer feedback on hotel booking websites support the decision-making process of the customer as the reviews provide a deeper understanding about all aspects of a hotel. Consequently, review and rating analyses are of great interest to consumers and hotel owners for the hotel related social media services. The key challenge, however, is to make the wide variety of information accessible in a simple, fast and relevant way and the solution is Topic Modelling and Opinion Mining. Common approaches like Latent Semantic Analysis (LSA) and Hierarchical Dirichlet Process (HDP) have order affects. If the input dataset is shuffled then different topics are generated leading to misleading results. To overcome this, a two-stepped feature engineering process is used: first step is to use a TF-IDF with modified trigrams calculation followed by the second step in removing weak features from the corpus thereby reducing the dimensionality of the Vector Space Model (SVM) for efficient Topic Modeling and sentiment analysis of the considered corpus. Sentiment score is calculated using VADER tool and Topic Modeling is done with Batch Wise Latent Dirichlet Allocation (LDA) using Stochastic Variational Inference (SVI) model. The modified trigrams included calculation of probabilities of words not only in the backward direction but also the probability calculation of the next two words of the target word thereby retaining its context information. The proposed method using Batchwise LDA with SVI along with two-stepped feature engineering process considerably improved its performance when compared to LSA and HDP models due to the fact of identifying hidden and relevant topics in terms of their optimized posterior distribution in hotel reviews dataset. The Batchwise LDA with SVI improved its performance by 3% in terms of its coherence values by using two-stepped feature engineering process and by 9% and 4% increase when compared with LSA and HDP models respectively.

358

Authors: Azad Raheem Kareem, Ali Majeed Mahmood

Direction of Arrival (DOA) estimation represents one of the key issues in the field of signal processing for the present and future 5G and radar engineering applications. The problem of the inaccuracy of DOA estimation has attracted considerable interest from academia. One of the advantageous common techniques that have been followed to improve the accuracy of DOA is the Estimation of the Signal Parameters via the Rotational Invariance Technique (ESPRIT) algorithm, albeit ESPRIT suffers from the challenge of estimation bias at short separation distances when two sources are very close to each other. Hence, in this paper, a modified-ESPRIT algorithm is proposed to improve the accuracy of the DOA. The modification of ESPRIT is presented by increasing the phase difference between the received signals. The idea is to add a pre-processing before the frame of the ESPRIT algorithm; this is done by introducing a double-balanced mixer and 90o signal splitter at the output of each antenna. The performance evaluation shows that using only the ESPRIT algorithm exhibits large estimation bias when two sources are very close to each other, while the performance is improved noticeably with the proposed modified-ESPRIT. It can detect and resolve two sources with an enhancement of 83.09% over traditional ESPRIT when the number of snapshots is very short, while an enhancement of 54.4% is achieved when source separation between (1 to 4) degrees and 77.8% achieved when Signal to Noise Ratio (SNR) between 0-10 dB and of 79.04% when four or fewer elements are used. The obtained results validate the performance efficiency of the proposed algorithm in terms of less Root Mean Square Error (RMSE), and a smaller number of snapshots.

378

Authors: Murtadha Al-Kaabi, Layth Al-Bahrani

Artificial Bee Colony (ABC) simulates the behaviour of intelligent foraging for a honeybee swarm. This article deals with one of the best swarm-based algorithms that has been used to solve the Optimal Power Flow (OPF) problem. Minimization of the objecting function can be satisfied by choosing a suitable optimal control variable while maintaining an acceptable system performance of the state variables in terms of their limits. The control variables that used in this article are the magnitude voltage of the generator, the tap changer of the transformer, the injection reactive power of compensative devise and the active power of the generator except the slack generator. The state variables are the reactive power of the generator, the load bus voltage and slack generator active power. The proposed algorithm modifies the classical Artificial bee colony by replacing the worst solutions obtained from the employee bees’ phase and the onlooker bees’ phase by the best solutions in the swarm size. The percentage of swarm sources that have been selected for the worst solutions is 33%, 50%, and randomly selection from the total source of the swarm size. This update contributes to improve the quality of solutions and determine the optimal settings of OPF control variables. The propose algorithm deals with minimization four different objective functions, the total fuel cost of the thermal units, the total active power losses in the transmission lines, the total emission caused by fossil-fueled thermal units and the total voltage deviation at the load buses. The modified ABC reduced the fuel cost by 11.34%, active power losses by 49.26%, voltage deviation by 91.34% and the emission by 16.70% satisfying all the constraint of the state variables in their limits. The proposed algorithm has been applied on the IEEE 30 bus system and gives good result when compare with other optimization techniques.

399

Authors: Mohammed K. Al-Haddad, Hadi T. Ziboon

Due to the inefficient use of the licensed frequency spectrum, a significant portion of the spectrum is left unutilized. This has led to the emerging of the Cognitive Radio (CR) as new technology that can access the white spaces in the licensed spectrum for improved spectrum utilization efficiency. In this paper, we present a scheme for detecting cyclostationary feature embedded in multicarrier signals like Orthogonal Frequency Division Multiplexing (OFDM) and Filter Bank Multicarrier (FBMC). The cyclostationary feature is generated due to the presence of pilot signals at certain subcarriers commonly used for channel estimation and frequency offset estimation. Therefore, no especial restrictions on the Primary User (PU) signal are imposed in order to generate the desired Cyclostationary Signature (CS). Both cases of scattered pilots and continuous pilots are considered. The algorithm is based on observing a periodic pattern in the cyclic autocorrelation function created by the pilot subcarriers, this periodic pattern is considered the cyclic signature and it can be extracted without prior knowledge of the signal parameters. The performance is evaluated under different impairments conditions like timing offset, frequency offset and multipath channel in addition to AWGN. Results show that FBMC has about 2-3dB signal-to-noise ration advantage over OFDM in continuous pilots mode and both modulations perform comparably in scattered pilots mode.

423

Authors: Berlian Al Kindhi

The stipulation of the COVID-19 (Corona Virus Disease 2019) as a global pandemic by the WHO (World Health Organization) made a number of countries lockdown. Countries like Italy, Denmark, China, and Ireland have taken lockdown steps to prevent this disease from spreading and taking many lives. COVID-19, SARS (Severe Acute Respiratory Syndrome), and MERS (Middle-East Respiratory Syndrome) are viral infections in the respiratory tract that can be fatal. SARS first became an epidemic in China in 2002, while MERS first appeared in the Middle East in 2012. At the end of 2019, a new disease appeared in China called COVID-19. These three viruses are still in the same family so they have very similar nucleotide sequences. The tested COVID-19 primer was able to adhere well with a similarity level of more than 70% in all DNA SARS and MERS isolates tested. To distinguish DNA samples between MERS, SARS, and COVID-19 using the basic local alignment sequence nucleotide approach alone is not enough. We propose an optimization of machine learning methods to predict the COVID-19, the optimization method depends on the method we improved. In Discriminant Analysis, we use Wilks Lamda's approach and change Linear into Diagonal Discriminant Matrix. In the Decision Tree method, we make optimization by making gain formulation to minimize the entropy value to get more information on the result. We optimized K-NN with add weighted distance optimization, and in SVM we try several kernels and optimize the hyperplane with SRM (Structural Risk Minimization) approach to looking for the best result. Besides that, in preparation for input features, we use Edit Levenshtein Method with the calculation of the optimum similarity from each DNA sequence. The results of our test, optimization of the Decision Tree method produces an accuracy of 98.3%, optimization of Discriminant Analysis 98.3%, and optimization of SVM and KNN 100% respectively. We also find a fact in the DNA Alignment process, when the primer being compared is 'R', the nucleotides in the COVID-19 sample data are always 'A' and this approach from the bioinformatic side can be used as analytical material in the medical world.

446

Authors: Salah Mahdi Hamzah, Ibrahim A. Murdas

Frees Space Optical (FSO) communication is one of the communication systems types that uses a free space to transmit information carried by light. It is previously known that the single input single output (SISO) technique is susceptible to atmospheric attenuation because of the effect of weather conditions. The proposed system is a combination of dense wavelength division multiplexing (DWDM) and multiple input multiple output (MIMO) techniques with Fork components. The main Fork component is configured in the Optisystem simulator to connect to another Fork components to increase the power of transmitted signals and ensure the arrival of the transmitted signals to the receiver of the FSO system. The key idea in the proposed system is to mitigate the attenuation that will be happened to the transmitted optical signal which propagated through free space due to different weather conditions. The study is done based on using the Optisystem simulation toolbox that is used to emulate different weather attenuation conditions in two types of FSO systems. The first is the traditional DWDM-SISO and the second is a proposed system named Hybrid DWDM-MIMO. A comparison between the proposed system and the traditional system is made in terms of the quality factor under different weather attenuation. The proposed system shows promising results in the performance and the quality of the received signal. The transmission path length of the proposed system under dense fog attenuation of 260 dB/km is enhanced to (30.43%) in comparison with traditional DWDM-SISO, also transmission path length of the proposed system under heavy rain attenuation of 9.29 dB/km is enhanced to (55.55%) in comparison with traditional DWDM-SISO. The transmission path length of the proposed system under heavy dry snow of attenuation of 131.835 dB/km is enhanced to (26.19%) in comparison with traditional DWDM-SISO.