Evaluation of Codebook Design Using SCMA Scheme Based on A_(n) and D_(n) Lattices

The sparse code multiple access(SCMA)scheme is a Non-Orthogonal Multiple Access(NOMA)type of scheme that is used to handle the uplink com-ponent of mobile communication in the current generation.A need of the 5G mobile network is the ability to handle more users.To accommodate this,the SCMA allows each user to deploy a variety of sub-carrier broadcasts,and several consumers may contribute to the same frequency using superposition coding.The SCMA approach,together with codebook design for each user,is used to improve channel efficiency through better management of the available spectrum.How-ever,developing a codebook with a greater number of value sets is still another challenge.With enhanced techniques of encoding and decoding for 5G networks,mapping the multidimensional constellations in the SCMA system plays a signif-icant role in improving the system performance and enhancing the overall system performance.The creation of a codebook utilizing the SCMA approach in con-junction with the lattice theory is suggested in this study.The prototype is shaped using a popular lattice,such as A n and D n,as the basis.Afterward,from the primary lattice constellation,the multidimensional complex mother constellation with the most noticeable variance in power is discovered.The lattice-based cod-ing is generated by combining the codebooks with the mother constellation,and the codes in the matrices are mapped by rotating the constellations in this context.The suggested technique,in conjunction with the investigation of novel SCMA codebook sets,provides improved performance in terms of Bit Error Rate(BER)and complexity with regard to Signal to Noise Ratio(SNR).Finally,the bit error rate is reduced for various SNRs during transmission in the channel.

Energy-Efficient Cluster in Wireless Sensor Network Using Life Time Delay Clustering Algorithms

Through Wireless Sensor Networks(WSN)formation,industrial and academic communities have seen remarkable development in recent decades.One of the most common techniques to derive the best out of wireless sensor networks is to upgrade the operating group.The most important problem is the arrangement of optimal number of sensor nodes as clusters to discuss clustering method.In this method,new client nodes and dynamic methods are used to determine the optimal number of clusters and cluster heads which are to be better organized and proposed to classify each round.Parameters of effective energy use and the ability to decide the best method of attachments are included.The Problem coverage find change ability network route due to which traffic and delays keep the performance to be very high.A newer version of Gravity Analysis Algorithm(GAA)is used to solve this problem.This proposed new approach GAA is introduced to improve network lifetime,increase system energy efficiency and end delay performance.Simulation results show that modified GAA performance is better than other networks and it has more advanced Life Time Delay Clustering Algorithms-LTDCA protocols.The proposed method provides a set of data collection and increased throughput in wireless sensor networks.

Smart Grid Communication Under Elliptic Curve Cryptography

Smart Grids(SGs)are introduced as a solution for standard power dis-tribution.The significant capabilities of smart grids help to monitor consumer behaviors and power systems.However,the delay-sensitive network faces numer-ous challenges in which security and privacy gain more attention.Threats to trans-mitted messages,control over smart grid information and user privacy are the major concerns in smart grid security.Providing secure communication between the service provider and the user is the only possible solution for these security issues.So,this research work presents an efficient mutual authentication and key agreement protocol for smart grid communication using elliptic curve crypto-graphy which is robust against security threats.A trust authority module is intro-duced in the security model apart from the user and service provider for authentication.The proposed approach performance is verified based on different security features,communication costs,and computation costs.The comparative analysis of experimental results demonstrates that the proposed authentication model attains better performance than existing state of art of techniques.

Micro Calcification Detection in Mammogram Images Using Contiguous Convolutional Neural Network Algorithm

The mortality rate decreases as the early detection of Breast Cancer(BC)methods are emerging very fast,and when the starting stage of BC is detected,it is curable.The early detection of the disease depends on the image processing techniques,and it is used to identify the disease easily and accurately,especially the micro calcifications are visible on mammography when they are 0.1 mm or bigger,and cancer cells are about 0.03 mm,which is crucial for identifying in the BC area.To achieve this micro calcification in the BC images,it is necessary to focus on the four main steps presented in this work.There are three significant stages of the process assigned to find the BC using a thermal image;the image processing procedures are described below.In the first stage of the process,the Gaussian filter technique is implemented to magnify the screening image.During the second stage,BC detection is separated from the pre-processed image.The Proposed Versatile K-means clustering(VKC)algorithm with segmentation is used to identify the BC detection form of the screening image.The centroids are then recalculated using proposed VKC,which takes the mean of all data points allocated to that centroid’s cluster,lowering the overall intracluster variance in comparison to the prior phase.The“means”in K-means refers to the process of averaging the data and determining a new centroid.This process eliminates unnecessary areas of interest.First,the mammogram screening image information is taken from the patient and begins with the Contiguous Convolutional Neural Network(CCNN)method.The proposed CCNN is used to classify the Micro calcification in the BC spot using the feature values is the fourth stage of the process.The assess the presence of high-definition digital infrared thermography technology and knowledge base and suggests that future diagnostic and treatment services in breast cancer imaging will be developed.The use of sophisticated CCNN techniques in thermography is being developed to attain a greater level of consistency.The implemented(CCNN)technique’s performance is examined with different classification parameters like Recall,Precision,F-measure and accuracy.Finally,the Breast Cancer stages will be classified based on the true positive and true negative values.

Application of Taguchi Method for the Optimization of System Parameters of Centrifugal Evaporative Air Cooler

A new evaporative cooling system based on the action of centrifugal forces is proposed.Such systems are suitable for cooling large air volumes in tropical climates.Effects of geometrical and operational parameters on system performance are optimized using Taguchi method.It is observed that disc speed,air flow rate and water flow rate are found to have major influence on system performance and other parameter,viz.,disc diameter,pin geometry,evaporation chamber length and orientation of pin have less influence.

Enhancement of Natural Circulation Type Domestic Solar Hot Water System Performance by using a Wind Turbine

Performance improvement of existing 200 litres capacity natural convection type domestic solar hot water system is attempted.A two-stage centrifugal pump driven by a vertical axis windmill having Savonius type rotor is added to the fluid loop.The windmill driven pump circulates the water through the collector.The system with necessary instrumentation is tested over a day.Tests on Natural Circulation System(NCS)mode and Wind Assisted System(WAS)mode are carried out during January,April,July and October,2009.Test results of a clear day are reported.Daily average efficiency of 25-28% during NCS mode and 33-37% during WAS mode are obtained.With higher wind velocities,higher collector flow rates and hence higher efficiencies are obtained.In general,WAS mode provides improvements in efficiency when compared to NCS mode.