Adaptive coding based quantum communication system for image
transmission over error-prone channels
Abstract
Adaptive coding in quantum communication offers a promising approach to
enhance the efficiency and reliability of data transmission using
quantum superposition, particularly in noisy and error-prone channels.
This study investigates the effectiveness of quantum communication
combined with adaptive coding for compressed image transmission using
Joint Photographic Experts Group (JPEG) codec and High Efficiency Image
Format (HEIF) with polar codes at varying rates. To maintain a similar
bandwidth, the source coding rates are adjusted according to the channel
coding rates. The results show that the adaptive coding based quantum
communication system significantly outperforms equivalent classical
systems, especially at low signal-to-noise ratios (SNR), achieving Peak
Signal-to-Noise Ratio (PSNR) improvements up to 65 dB and Structural
Similarity Index Measure (SSIM) values up to 0.9999 for HEIF images and
PSNR values up to 58 dB with SSIM values up to 0.9994 for JPEG images.
These findings demonstrate the superior robustness and higher image
quality of adaptive coding based quantum communication in varying
channel noise conditions and bandwidth restricted applications.