Telecommunications

Aug 23


The IUP Journal of Telecommunications

ISSN: 0975-5551

A 'peer reviewed' journal indexed on Cabell's Directory, and also distributed by EBSCO and Proquest Database

It is a quarterly journal that publishes multidisciplinary research papers encompassing conceptual, theoretical and empirical studies relating to: Modeling, analysis, design and management of telecommunication systems; Transmission systems and Signaling system; Time division switching systems; Radio waves, Radar imaging, Satellite communication; Artificial Intelligence; Fibre optics and Photonic switching; Performance evaluation of Wide Area and Local Networks; Security issues of Mobile Networks; Standardization and regulatory issues, etc.

Privileged access to Online edition for Subscribers.

Focus Areas
  • Broadband Communication Systems
  • Wireless Communication Networks
  • Optical Communication
  • Satellite Communications
  • Target Detection and Tracking
  • Intelligent Networks and Services
  • Internet Protocol Design and Traffic Analysis
  • Digital Image Processing
  • Multi-User Detection Techniques
  • Radar and Sonar Technologies
  • VLSI Designing
  • Digital Audio Broadcasting System
  • Multiplexing Queuing Theor
CheckOut
Article   Price (₹) Buy
Setting Up a VoIP Phone System Using Open Source Tools
50
Mobile IP Framework for Seamless Global Roaming Across Heterogeneous Networks
50
Accurate EEG-Based Emotion Detection Using Feature Optimization and Machine Learning Algorithm
50
     
Contents : (Aug 2023)

Setting Up a VoIP Phone System Using Open Source Tools
G P D Chamoth Madushan Jayasekara

Voice over Internet Protocol (VoIP) is simply the transport of voice traffic over the Internet or any IP-based packet-switched network. This is in contrast with the traditional telephone network, carrying voice data over dedicated circuit-switched transmission lines. A major challenge to implementing VoIP is to ensure sufficient bandwidth, and access to the available bandwidth is controlled and prioritized. Sufficient bandwidth is required to maintain high-quality voice. On the other hand, controlling it limits bandwidth-hogging applications and guarantees access to delay-sensitive applications. The objective of this paper is to familiarize the readers with building a test VoIP lab setup using open-source tools; experimenting how different network impairments would affect VoIP quality; and explaining the lab setup activities, investigations, data analysis and research. Subsequently, the paper gives an overview of various technicalities such as operating system, servers, codec selection, signaling protocols, etc. involved in achieving network quality-of-service.


© 2023 IUP. All Rights Reserved.

Article Price : ₹ 50

Mobile IP Framework for Seamless Global Roaming Across Heterogeneous Networks
Fidelis I Onah

With the appearance of more and more bandwidth consuming applications in today's mobile data services market, telecom operators can no longer rely on price to attract and retain subscribers. Seamless roaming has become an important value-added service for improving back-end billing, subscriber relationships, bandwidth preservation through aggregation, quality of service and revenue generation. The paper presents the Mobile IP framework and methodology for supporting seamless global roaming within a geographic mobility domain. The goals and challenges of secured and seamless roaming solution are investigated. The responsibility of individual layers of the TCP/IP protocol stack is ill-defined with respect to mobility. The paper highlights the need for an adaptive generic algorithm to select, optimize and maintain transparent network connectivity for mobile users on the move, despite changing connection types and locations in a heterogeneous network environment.


© 2023 IUP. All Rights Reserved.

Article Price : ₹ 50

Accurate EEG-Based Emotion Detection Using Feature Optimization and Machine Learning Algorithm
Nayana Vaity and Ankit Temurnikar

This paper proposes a feature optimization and detection method based on the bee scout algorithm and derived support vector machine (DSVM). The DSVM approach reduces network training time by removing unused features. First, the raw EEG data is decomposed using discrete wavelet transform (DWT) into a sequence of frequencies. Before the feature extraction procedure, the spatiotemporal component of the decomposed EEG signal is represented as a two-dimensional spectrogram using the shifting. To extract features, four pre-trained SVMs are employed. Dimensional reduction and feature selection are accomplished by bee scout-based EEG channel selection and DSVM approach. The proposed algorithm is tested on MAHNOB dataset. The results suggest that the proposed algorithm is more efficient than existing algorithms.


© 2023 IUP. All Rights Reserved.

Article Price : ₹ 50