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Showing posts with label Google Scholar. Show all posts
Showing posts with label Google Scholar. Show all posts

Enhancing Scalability and Privacy in 5G-Enabled IoT Networks through Block chain Integration and AI Solutions - Indexed in Google Scholar : IJISEA

The proliferation of Internet of Things (IoT) devices in the digital landscape has ushered in a new era of connectivity, empowering billions of devices to communicate over the internet. However, the reliance on centralized protocols for data transfer poses significant security challenges. The emergence of 5G technology promises high-speed data transfer, yet it also underscores the need for robust security measures. Integrating Artificial Intelligence (AI) with 5G networks offers solutions to various challenges, including security concerns and the demand for autonomous systems like self-driving vehicles and virtual reality applications. Blockchain technology, known for its decentralized ledger system, presents an opportunity to address security and trust issues in IoT environments. However, integrating blockchain with IoT networks presents its own set of challenges, particularly in terms of throughput limitations. This paper addresses these challenges by proposing a solution that combines a Blockchain Distributed Network with the Raft consensus algorithm to enhance network scalability and throughput. Additionally, privacy concerns inherent in blockchain ledgers are addressed using zkLedger, a zero-knowledge based cryptographic solution. Through these innovations, this research contributes to the development of secure, scalable, and privacy-preserving 5G-enabled IoT networks.

 Key words: Blockchain, Artificial Intelligence, Internet of Things, 5G Network, Scalability, Privacy. Abbreviations: Blockchain (BC), Artificial Intelligence (AI), Internet of Things (IoT), 5G Network, Scalability (SC), Privacy (PR).

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Indexed in - Google Scholar

Optimization of PAPR in OFDM using Orthogonal Selective Level Mapping (SLM)

Indexed in - Google Scholar

Abstract— To optimize the PAPR in conventional OFDM, Low Complexity Selective Level Mapping (SLM) is considered in this paper as it reduces PAPR significantly without loss of information. Orthogonal Frequency Division Multiplexing (OFDM) is the multicarrier modulation techniques, and it provides the provides the high spectral efficiency, low complication in implementation, less sensitivity to echoes and distortion. Due to these advantages of OFDM system is vastly used in various communication systems. But the major drawback of OFDM system is increase in peak power due to coherent addition of sub carriers. OFDM signal is the sum of many independently modulated sinusoidal waves and the amplitude is almost Rayleigh distribution. Amplitude of OFDM signal shows strong fluctuations and the resultant high Peak-to Average. Several techniques have been proposed to reduce PAPR, Low Complexity SLM can be employed in this paper to reduce PAPR in an OFDM system. In Low complexity SLM, PAPR can be reduced by multiplying the original signal with Orthogonal vector and generate statistically independent sequences which represent the same information before IFFT operation in OFDM system. The resulting independent data blocks are then forwarded into IFFT operation simultaneously and generate OFDM signal sequences.

After that compute the PAPR for all the OFDM signal sequences. Finally, the one sequence with the smallest PAPR will be selected for transmission. The proposed SLM scheme achieves similar PAPR reduction performance with much lower computational complexity compared with the conventional SLM scheme. The performance of the proposed SLM scheme is verified with various modulation schemes. The results are simulated using MATLAB.

Keywords— Selective Level Mapping (SLM), OFDM, Peak to Average Power Ratio



Published : International Journal with ISSN Number

Published : International Journal with ISSN Number

Digital Image Processing - Research Opportunities and Challenges

Interest in digital image processing methods stems from two principal application areas: improvement of pictorial information for human interpretation; and processing of image data for storage, transmission, and representation for autonomous machine perception. The objectives of this article is to define the meaning and scope of image processing, discuss the various steps and methodologies involved in a typical image processing, and applications of image processing tools and processes in the frontier areas of research.

Key Words: Image Processing, Image analysis, applications, research.

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