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In modern wireless communication scenarios, non-orthogonal multiple access (NOMA) provides high throughput and spectral efficiency for fifth generation (5G) and beyond 5G systems. Traditional NOMA detectors are based on successive interference cancellation (SIC) techniques at both uplink and downlink NOMA transmissions. However, due to imperfect SIC, these detectors are not suitable for defense applications. In this paper, we investigate the 5G multiple-input multiple-output NOMA deep learning technique for defense applications and proposed a learning approach that investigates the communication system’s channel state information automatically and identifies the initial transmission sequences. With the use of the proposed deep neural network, the optimal solution is provided, and performance is much better than the traditional SIC-based NOMA detectors. Through simulations, the analytical outcomes are verified.

In the present situation, the healthcare sector is one of the leading areas in which technologies and data are easily improved. The vast volume of medical data is impossible to manage. Big data processing makes it easy to manage these data. There are several medical methods worldwide for many diseases. Machine learning is an emerging solution to disease detection and prediction. This document explains the diagnosis of disease through machine learning based on symptoms. Algorithms such as Naive Bayes, Decision Tree and the Random Forest are used in a given data collection and estimate of disease machines. The python programming language is used to execute it. The analysis demonstrates the proper detailed algorithm. By the data set the accuracy of an algorithm is determined.

The Internet-of-Things (IoT) will connect different types of cyber physical systems that are supported by different wireless transmission technologies, e.g., Wi-Fi, ZigBee, etc. However, the security protocols of those wireless technologies cannot be implemented to support seamless and secure IoT communications. Moreover, security protocols need to be light-weighted since some IoT devices have limited computation resources. In this research work, we propose a light weight physical-layer security-based authentication and key generation scheme The Internet-of-Things (IoT) will connect different types of cyber physical systems that are supported by different wireless transmission technologies, e.g., Wi-Fi, ZigBee, etc. However, the security protocols of those wireless technologies cannot be implemented to support seamless and secure IoT communications. Moreover, security protocols need to be light-weighted since some IoT devices have limited computation resources. In this research work, we propose a light weight physical-layer security-based authentication and key generation scheme to bridge different transmission technologies in IoT communications. In the studied scenario, a group certificate is generated based on physical-layer information, i.e., Received Signal Strength (RSS) for all legitimate IoT devices in a network. The group certificate is to support mutual authentication between any pair of IoT devices within the network. Furthermore, the proposed scheme also generates a session key for the authenticated pair of IoT devices for other purposes of security features. The proposed scheme also addresses the issue of access control for new IoT devices with a short-term session key generation process. Security analysis is provided to show the efficacy of the proposed scheme against eavesdropping and replay attacks. A tested based experiment is conducted to further demonstrate the RSS based value generation and distribution.

Finding the privileged implementational model for the Internet of Things (IoT) applications is one of the present difficulties in the field of healthcare. The blend with healthcare will just make this test progressively troublesome. IoT is as yet an underinvestigated territory and healthcare is a perplexing segment with a ton of government contribution, which makes business development in this part increasingly troublesome. In any case, organizations can effectively make plans of action to help their IoT application. IoT is a mechanical empowering agent and plan of action advancement is one of them alongside a worthy system as a business foundation whose constituent organizations have reliably troublesome, and strengthening monetary models. Obviously, one organization alone cannot totally develop healthcare applications. A decent communication with various consideration suppliers and the safety net providers is required to such an extent that a worthy system exists through which care is conveyed. This is additionally called a business biological system, which compares to the requirement for an IoT environment. Accordingly, the accomplice system building square will be a significant perspective when building up a plan of action for organizations with an IoT application in healthcare. Other than these components, there falsehoods the requirement for administrative changes and new industry gauges to encourage change in the new business. The literature presented in this chapter introduces an insight into the challenges that different organizations are looking for building up an IoT application in healthcare. This will require open inquiries because IoT is an ongoing marvel, and it is unsure how organizations in this setting right now work since there are just a set number of them. This exploratory point of view has the preferred position that it is conceivable to alter the course, in view of new experiences while leading examination which ends up being vital.

A novel microstrip bandpass filter with split ring resonator (SRR) defected ground structure (DGS) patch antenna for computational applications is proposed in this article. This filter and antenna design can collaboratively work as filtenna for improved performance by minimizing the total power consumption in the system. The investigation is carried out on width of the slit opening of SRR slot (W) and rotation of the inner square-shaped ring structure in clockwise direction. The proposed filtenna is designed to provide a tunable frequency operation. Simulation is performed on high-frequency structural simulator (HFSS) which demonstrates good output response making filtenna design suitable for intelligent vehicular communication and wireless local area network (WLAN) applications. The proposed filtenna is compact in size, has low insertion loss, exhibits high selectivity, and demonstrates excellent out-of-band performance.