International Journal of Research in Advanced Electronics Engineering
2025, Vol. 6, Issue 2, Part A
Design and optimization of 5G antenna arrays for high-gain millimeter-wave communication systems
Author(s): Liang Chen, Ying Zhang and Jiawei Wu
Abstract: The rapid proliferation of Internet of Things (IoT) devices equipped with embedded vision sensors has intensified the need for real-time, low-power image compression architectures that can operate efficiently under constrained resources. This study presents the design and evaluation of a Low-Power VLSI Architecture for Real-Time Image Compression in IoT Edge Devices, integrating algorithm-hardware co-design with advanced power optimization techniques. The proposed system employs a hybrid compression kernel based on simplified transform and quantization modules, optimized through dataflow restructuring and memory-efficient processing. Hardware-level strategies such as dynamic voltage scaling, clock gating, and multi-threshold CMOS design were implemented to minimize both dynamic and leakage power dissipation. Experimental evaluations on standard image datasets demonstrate that the proposed architecture achieves an average Peak Signal-to-Noise Ratio (PSNR) of 35 dB and a Structural Similarity Index Measure (SSIM) of 0.95, comparable to conventional JPEG2000 implementations, while reducing energy-per-frame consumption by up to 60%. Throughput results confirm real-time operation exceeding 60 frames per second (fps) at VGA resolution and maintaining above 30 fps for HD resolutions, validating the design’s scalability for diverse IoT environments. The hardware prototype synthesized in 65 nm CMOS technology occupies a compact area of 1.25 mm², making it suitable for integration in edge System-on-Chip (SoC) platforms. Statistical analysis using one-way ANOVA revealed significant differences among compression architectures in both image quality and energy consumption, confirming the efficiency of the proposed design. The research concludes that a well-structured combination of algorithmic simplification and hardware-level power optimization can yield substantial performance benefits, offering a robust pathway toward sustainable and intelligent edge computing. The proposed architecture thus represents a practical advancement for IoT-based visual systems, balancing computational performance, energy efficiency, and integration feasibility for next-generation low-power embedded imaging applications.
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How to cite this article:
Liang Chen, Ying Zhang, Jiawei Wu. Design and optimization of 5G antenna arrays for high-gain millimeter-wave communication systems. Int J Res Adv Electron Eng 2025;6(2):01-05.
