Bibhu Prasad Ganthia, Rosalin Pradhan | International Journal of Digital Communication and Analog Signals | Vol 12, Issue 01 | ISSN: 2455-0329
Abstract
The rapid advancement of next-generation wireless technologies such as 5G and 6G has created an increasing demand for high data rates, low latency, and energy-efficient communication systems. Conventional digital signal processing techniques, while flexible and accurate, often suffer from high computational complexity and power consumption, whereas analog signal processing provides low-latency and energy-efficient solutions but lacks adaptability and robustness. This paper proposes a novel hybrid digital–analog signal processing framework that integrates the strengths of both domains to enhance data transmission performance in modern wireless communication systems. The proposed approach employs analog front-end processing for signal amplification, filtering, and noise reduction, combined with digital back-end processing for modulation, encoding, and error correction. The framework is evaluated through simulation using MATLAB, considering parameters such as bit error rate, spectral efficiency, and transmission latency. Results demonstrate that the hybrid model significantly improves system performance compared to conventional methods, offering reduced power consumption and enhanced reliability under varying channel conditions. Additionally, the suggested architecture facilitates adaptive communication techniques that enhance overall communication efficiency by dynamically optimising signal processing activities based on network needs and channel quality. The paper also emphasises the prospective uses of hybrid digital-analog processing in satellite communication, Internet of Things networks, autonomous communication systems, and upcoming intelligent wireless infrastructures. This work provides a scalable and efficient solution for future high-speed communication networks.
Keywords- Hybrid Signal Processing, Wireless Communication, Analog–Digital Integration, Spectral
Efficiency, Bit Error Rate, Low-Latency Systems
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