The study explores about the Wireless communication which is one of the most rapidly evolving and active technology fields in the communication world. Wireless communication is a means of transmitting data from one point to another without the use of wires, cables, or another physical medium. As a result, commercial network operators have risen at an accelerating rate, bringing in the era of big data. Machine learning has been applied in a range of corporate and academic research contexts as one of the most promising artificial intelligences (AI) methods for deciphering this deluge of knowledge. This study presents a high-level introduction of big data handling and technological advances, as well as their potential applications in next-generation wireless networks (NG). Following that, we employ advanced analytics to estimate mobile users' demands and then use that knowledge to improve the efficacy of “community wireless communication channels.” In specifically, a unified, huge data-aided computer learning framework comprised of feature extraction, data modelling, and prediction/online refinement is provided. The primary benefits of the proposed framework are that we could create the logic, problem formulations, and method of powerful computational models inside the frame of wireless networks by depending on vast data that reflects the both spectrum and other hard demands of users. Via general, information is conveyed from sender to receiver across a certain distance in a communication system. The transmitter may be located anywhere within a few meters using Wireless Communication… We examined currently known approaches and explored their benefits and drawbacks in order to identify new research avenues for future advancements in underwater sensor networks.

A study on the adoption of Wireless Communication in Big Data Analytics Using Neural Networks and Deep Learning

A safe and reliable in vivo nanoscale communication network will be of great benefit for medical diagnosis and monitoring as well as medical implant communication. This review article provides a brief introduction to nanoscale and molecular networking in general and provides opinions on the role of active networking for in vivo nanoscale information transport. While there are many in vivo communication mechanisms that can be leveraged, for example, forms of cell signaling, gap junctions, calcium and ion signaling, and circulatory borne communication, this review examines two in particular: molecular motor transport and neuronal information communication. Molecular motors transport molecules representing information and neural coding operates by means of the action potential; these mechanisms are reviewed within the theoretical framework of an active network. This review suggests that an active networking paradigm is necessary at the nanoscale along with a new communication constraint, namely, minimizing the communication impact upon the living environment. The goal is to assemble efficient nanoscale and molecular communication channels while minimizing disruption to the host organism.

Toward in vivo nanoscale communication networks: utilizing an active network architecture

This research examines way to pass, among the most dynamic and quickly-evolving technology fields in the telecommunication sector. Data may be sent between two locations wirelessly without the usage of digital downloads like wires and cables. Business telecom companies have advanced as a consequence and joined the big data age. Among the most potential machine learning methods for interpreting this deluge of information is computer science, which is employed in a range of business and scholarly research situations. This paper gives a broad overview of technology advancements and big data analytics, as well as possible uses for them in succeeding cellular networks. Apply sophisticated analytics to determine what mobile users' demands are, and then utilise that information to raise the effectiveness of "social wireless channels of communication." The huge, integrated, information machine educational approach it offers, which consists of extracting the features, simulation models, and forecasting enhancements, is particularly noteworthy. The key benefit of the proposed methodology is the logic of robust mathematical methods, issue conceptualization within the context of cellular networks, and reliance on a vast amount of data that represents both the bandwidth as well as other stringent user needs. and the ability to create a procedure. In a communication network, data is normally sent from the transmitter to the receiver across a distance. Using communication systems, the transmitter may be positioned somewhere within a few metres. We will examine existing strategies, their advantages and disadvantages, and potential developments in underwater sensors right now. We had discovered a fresh method of investigation.

Application of Neural Network in the Prediction Models of Machine Learning Based Design

This research examines way to pass, among the most dynamic and quickly-evolving technology fields in the telecommunication sector. Data may be sent between two locations wirelessly without the usage of digital downloads like wires and cables. Business telecom companies have advanced as a consequence and joined the big data age. Among the most potential machine learning methods for interpreting this deluge of information is computer science, which is employed in a range of business and scholarly research situations. This paper gives a broad overview of technology advancements and big data analytics, as well as possible uses for them in succeeding cellular networks. Apply sophisticated analytics to determine what mobile users' demands are, and then utilise that information to raise the effectiveness of "social wireless channels of communication." The huge, integrated, information machine educational approach it offers, which consists of extracting the features, simulation models, and forecasting enhancements, is particularly noteworthy. The key benefit of the proposed methodology is the logic of robust mathematical methods, issue conceptualization within the context of cellular networks, and reliance on a vast amount of data that represents both the bandwidth as well as other stringent user needs. and the ability to create a procedure. In a communication network, data is normally sent from the transmitter to the receiver across a distance. Using communication systems, the transmitter may be positioned somewhere within a few metres. We will examine existing strategies, their advantages and disadvantages, and potential developments in underwater sensors right now. We had discovered a fresh method of investigation. 

Molecular communications (MC) is a bio-inspired paradigm that aims to utilise molecules to exchange information among nano-machines. Given the tiny devices used in a MC system and the feasibility of MC in biological environments, MC can be applied to many applications ranging from the healthcare to manufacturing fields.

In order to better realize these applications in the future, this Ph.D. research is dedicated to the investigation of a more functional, precise and reliable Diffusion-based Molecular Communications (DBMC) system. To achieve this goal, the contributions of this thesis are as follows. Firstly, the point-to-point (PTP) DBMC system with the absorbing receiver model is established and investigated. A study of the accuracy of the analytical channel model is also introduced. Secondly, dependent on different types of the transmitter (TX) and receiver (RX), three different communication scenarios are proposed. Thirdly, to enhance the reliability of the information at RX, the Error Correction Codes (ECCs), as the most prominent technique is employed within the DBMC system to control or correct any errors introduced during the transmission process. Fourthly, due to the limitation of the power budget of the nano-machines, the energy efficiency of the system is also taken into account. Finally, a two-receiver broadcast DBMC system is established with an absorbing interfering receiver (RI) and an absorbing target receiver (RT). By analysing the performance of the communication link between TX and RT (target communication link), the impact of the positions of RI on RT is studied.

This study indicates that the application of ECCs does enhance the performance of PTP DBMC systems. In addition, the encoder and decoder design, and the BER performance are shown to be the two primary factors for selecting the most suitable ECC for the application. Finally, considering a two-receiver broadcast DBMC system with absorbing receivers, the existence of RI does affect the performance of the target communication link which is crucial result for the field moving forward.

Error correction codes for molecular communication systems

Wireless ad hoc communication on the nanoscale will require thinking outside of the traditional radio spectrum. New applications will utilize new forms of wireless communication channels. For example, nanoscale communication will enable precise mechanisms for directly interacting with cells in vivo. Information may be sent to and from specific cells within the body, allowing detection and healing of diseases on the cellular scale. From a medical standpoint, the use of current wireless techniques to communicate with implants is unacceptable for many reasons, including bulky size, inability to use magnetic resonance imaging after implantation, potential radiation damage, surgical invasiveness, need to recharge/replace power, post-operative pain and long recovery times, and reduced quality of life for the patient. Better, more human in vivo implant communication is needed. Development of both biological and engineered nanomachines is progressing; such machines will need to communicate. Unfortunately, networking vast collections of nanoscale sensors and robots using current techniques, including wireless techniques, is not possible without communication mechanisms that exceed nanoscale volumes.

S. Bush

Papers

Wireless ad hoc nanoscale networking