3 publications
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Published Subscription
Design and Simulation of Compact Microstrip Patch Antennas for 5G ApplicationsBy Bhavisha Vishalbhai Parvadiya
Abstract: The rapid growth of fifth-generation (5G) wireless communication systems has created significant demand for compact, high-gain, low-profile, and energy-efficient antenna technologies. Microstrip patch antennas have emerged as one of the most suitable antenna structures for 5G applications because of their lightweight design, low fabrication cost, compact size, ease of integration, and compatibility with modern wireless devices. However, conventional microstrip patch antennas suffer from limitations such as narrow bandwidth, low gain, …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 1, 2026 · pp. 1–16 Read article →
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Published Subscription
Performance Analysis of Hybrid Signal Processing Methods in Modern Communication NetworksBy Bhavisha Vishalbhai Parvadiya
Abstract: Modern communication networks require high-speed, reliable, and energy-efficient signal transmission for applications such as wireless communication, satellite systems, Internet of Things (IoT), smart healthcare, and next-generation 5G/6G networks. Traditional signal processing techniques often face limitations in dynamic communication environments due to interference, noise, latency, and bandwidth constraints. Hybrid signal processing methods combine multiple techniques including analog-digital processing, adaptive filtering, beamforming, machine learning, and intelligent optimization to enhance communication performance and …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 1, 2026 · pp. 22–35 Read article →
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Published Subscription
Hybrid Evolutionary Algorithm for Automated Test Case Generation in Large-Scale Software SystemsBy Bhavisha Vishalbhai Parvadiya
Abstract: Automated test case generation is a crucial activity for ensuring the reliability, robustness, and quality of large-scale software systems. Conventional test generation techniques often face significant challenges in handling scalability, achieving high code coverage, and adapting to complex and heterogeneous software architectures. Evolutionary algorithms have emerged as effective solutions, capable of exploring large search spaces and generating test suites with improved coverage and fault detection capabilities. However, individual evolutionary strategies, …
Published in International Journal of Software Computing and Testing · Vol. 12, Issue 1, 2026 · pp. 15–21 Read article →