Devasis Pradhan

The paper mainly focuses on the channel coding design for high-speed telecommunication systems. The challenging issues in this study are based on (1) the growing demand for high data speed and an increase in subscribers, and (2) high-speed telecommunication networks allow users to avoid them due to better speed and more bandwidth. The objectives of this study are (1) to obtain a higher data rate, higher spectral efficiency, higher throughput, higher bandwidth, and higher energy efficiency at lower latency and (2) to detect/correct errors caused when information is transmitted through noisy channels. Therefore, high-speed telecommunication channel coding techniques will play a major role in achieving fast communication with minimum errors. The linear block and turbo codes are fundamental to analyzing the channel coding scheme for specific purposes. Theoretical concepts with numerical simulation are used to conduct the analyses. The simulation results on BER analyses confirm that the performance criteria could be met with real-world applications.

The paper mainly focuses on the physical characteristics analysis of an intelligent reflecting surface for high-speed telecommunication networks. The research problem in this study are (i) To overcome the bottleneck, a novel transmission scheme, named hybrid reflection modulation (HRM) must be considered, exploiting both active and passive reflecting elements at the RIS and their combinations, which enables to convey information without using any radio frequency (RF) chains, (ii) In the HRM scheme, the active reflecting elements using additional power amplifiers can be able to amplify and reflect the incoming signal, while the remaining passive elements can reflect the signals with appropriate phase shifts, (iii) Based on this novel transmission model, we will observe an upper bound for the average bit error probability (ABEP), and derive achievable rate of the system using an information theoretic approach, and (iv) Moreover, comprehensive computer simulations could be performed to prove the superiority of the proposed HRM scheme over existing fully passive, fully active and reflection modulation (RM) systems. The research directions are as follows: (i) Implementing the Intelligent Reflecting Surfaces (IRS) and Hybrid Reflection Modulation Technologies for 6G Wireless Communication, (ii) Implementing the Intelligent Reflecting Surfaces (IRS) and Hybrid Reflection Modulation Technologies with physical layer security techniques, and (iii) Modelling the mathematical equation for optimization design of IRS system. There are two portions in this study. The first is designing the signal model in the IRS surface with specific physical parameters. The second one is an analysis of the capacity of point-to-point MIMO channels. The analyses are conducted using by MATLAB language. The results confirm the performance specification of the IRS system for high-speed telecommunication applications.

The paper emphasizes on the analysis on wideband channel model for high speed wireless communication systems. The research problem in this study are based on the following concepts such as (i) Firstly, it is necessary to change to the appropriate physical devices that can support 5G system, (ii) It is required to design a channel that will adapt to the medium that will be convenient for the changed physical devices, and (iii) Mobile terminals that currently use 4G cannot be used in 5G system. The objectives in this study are - to analyze the existing channel model for mobile communication, to analyze the mathematical and dynamical model for wireless propagation channel, to implement the wireless propagation channel with specific purposes, to implement the optimized channel model performance, and to evaluate the performance of the developed channel design. The numerical analyses in this study are conducted by using MATLAB language. The research direction in this study are based on the channel system functions, and tapped delay-line models. The simulation results are confirmed that the 12 taps in this study for the high speed wireless communication system design.

The efficacy of the vehicular networks is highly dependent on the choice of communication models. The vehicular network communication models outline the nature of interactions between the entities of vehicles, infrastructure, and the environment. Some of the most common communication models in existence are Vehicle-to-Vehicle, Vehicle-to-Infrastructure, Vehicle-to-Grid, and Vehicle-to-Network. These models are categorized based on the entities involved, direction, and purpose of communication. The choice-making of these communication models are hurdled by the primary challenges of heterogeneity of applications and dynamic network conditions. This chapter proposes solutions to these challenges by constructing a fuzzy-based multi-criteria decision-making method of LBWA (Level Based Weighting Assessment). This fuzzy model considers the factors to be taken into account in selecting the vehicular network communication models and also determines the weightage to each of the factors considered. This model developed in this chapter facilitates identifying the most significant factors in selecting the communication models. The optimal ranking of the factors is validated with other decision methods to determine the consistency of the results. The chapter concludes with future research directions.

The paper mainly focuses on analyzing high-performance step-down DC to DC converter based on zero voltage switching with pulse width modulation technique for electric vehicles. In this paper, PI, fuzzy PI, and adaptive network-based fuzzy inference system (ANFIS)control methods are applied to the phase shift full-bridge (PSFB) zero voltage switching (ZVS) converter for auxiliary components in electric vehicles. The robust analysis of three control methods is compared by using the AC small-signal mathematical model. Traditional PI control uses specific mathematical equations with errors and derivatives. Fuzzy PI control utilizes fuzzy logic rules with linguistic variables such as high, medium, and low. ANFIS combines fuzzy logic and neural networks to capture both benefits. The three control designs' switching losses and load changes are analyzed and implemented with the MATLAB/SIMULINK Software platform. From the simulation results, traditional PI control works with 92% efficiency. Fuzzy PI control and ANFIS work with 93% efficiency at full load capacity.