Hybrid Quantum-Inspired Signal Processing Model for Secure Image Transmission in Next-Generation Communication Networks

Abstract

The transmission of images is now an urgent problem of the next-generation communication networks because of the growing cyber threats and the need to exchange data in real-time and high-resolution. Conventional models of signal processing that rely on encryption demand a high computational cost, have poor scalability, and are susceptible to new quantum attacks. The present paper is a suggestion to develop a Hybrid Quantum-Inspired Signal Processing Model combining quantum-secure hashing, hybrid Quantum Key Distribution (QKD), and quantum-inspired compression with classical signal processing methods. The suggested framework offers a better level of encryption protection but does not decrease computational performance. Simulated network evaluation under 5G network conditions reveals that the model is able to support a transmission rate of 15 Mbps, bandwidth efficiency of 85 %, and an image quality of 30 dB SNR, and limit the computational overhead to 50 ms. These findings point to the enhanced latency work and enhanced security of traditional approaches. The error correction, which is quantum-inspired, further minimizes the transmission errors and increases reliability. As the results have confirmed, the proposed hybrid model offers a scalable and safe solution to real-time image transmission in the advanced communication system and can be resistant to classical and quantum-based cyber threats.