Abstract The introduction of quantum communications, enabled by advancements in quantum computing, is expected to play a significant role in the field of communications. Inherent properties of quantum objects, such as superposition and entanglement, have the potential to provide novel solutions to overcome the challenges encountered by classical communication systems in bandwidth‐intensive applications such as media transmission. This research explores the performance of a quantum communication system in image transmission using quantum superposition and investigates its performance using a simple quantum channel model. With an increase in channel noise, there are significant gains in the rate distortion performance of images transmitted over the quantum channel compared to an ideal classical channel. This novel attempt at constructing a quantum communication‐based image transmission system indicates the potential of the approach to be applied to satisfy the ever‐increasing demands of high‐quality media transmission applications.
Abstract The introduction of quantum communications, enabled by advancements in quantum computing, is expected to play a significant role in the field of communications. Inherent properties of quantum objects, such as superposition and entanglement, have the potential to provide novel solutions to overcome the challenges encountered by classical communication systems in bandwidth‐intensive applications such as media transmission. This research explores the performance of a quantum communication system in image transmission using quantum superposition and investigates its performance using a simple quantum channel model. With an increase in channel noise, there are significant gains in the rate distortion performance of images transmitted over the quantum channel compared to an ideal classical channel. This novel attempt at constructing a quantum communication‐based image transmission system indicates the potential of the approach to be applied to satisfy the ever‐increasing demands of high‐quality media transmission applications.
ABSTRACT Quantum communication offers unparalleled reliability and efficiency, making it a promising solution for high‐quality media transmission. To explore this potential, we propose a quantum communication system for image transmission, addressing the challenges of transmitting high‐quality image data over error‐prone channels. A crucial aspect of advancing this field is quantum channel coding, specific to quantum systems. Therefore, this research evaluates the performance of low‐complex three‐qubit quantum error correction code for image transmission over noisy channels. JPEG and HEIF images are encoded using three‐qubit error correction method and compared to 1/3 rate polar codes with equivalent bandwidth. Results show that the three‐qubit error correction code significantly outperforms advanced classical polar codes in both classical and quantum domains, achieving a maximum PSNR of 64.5 dB (SSIM = 0.9997) in HEIF and 58.3 dB (SSIM = 0.9994) in JPEG. These findings underscore its potential as a robust solution for quantum communication in media transmission.
Quantum communication offers transformative potential for media transmission by addressing the limitations of classical communication systems. To realize this potential, the study proposes a quantum communication framework for transmitting compressed videos over error-prone channels, leveraging quantum superposition. Two channel coding schemes are analyzed: quantum error correction (three-qubit, five-qubit, and seven-qubit codes) and classical error correction (1/3 rate polar code), all operating within the same bandwidth constraints. The proposed systems are benchmarked against a classical communication system using 1/3 rate polar codes. Results show that the three-qubit error correction-based quantum communication system, while simple and efficient, achieves significant performance gains over both classical error correction-based quantum and classical communication systems, with up to 41.42 dB in peak signal-to-noise ratio (PSNR), 0.9639 in structural similarity index measure (SSIM), and 94.4042 in video multimethod assessment fusion (VMAF). However, the five-qubit and seven-qubit systems outperform the three-qubit system, with the seven-qubit system surpassing all others in high noise environments, demonstrating its robustness across various group of pictures (GOP) formats. These findings highlight the trade-offs between simplicity and complexity, as the three-qubit system is practical and efficient, while the five-qubit and seven-qubit channel codes offer higher fidelity and resilience at the cost of increased complexity.
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.
Quantum communication systems have the potential to revolutionize media transmission technologies with unparalleled efficiency and reliability. However, practical and scalable implementations are challenged by issues such as channel fading and interference. To address these, we propose a novel approach combining quantum superposition with transmit and receive diversity schemes in Multiple-Input Multiple-Output (MIMO) systems, designed to mitigate the effects of fading for enhanced image transmission. In our simulations, images in JPEG and HEIF formats are channel encoded with rate 1/2 polar coding, converted into qubit superposition states, and transmitted through a 2x2 MIMO system with varied diversity schemes. At the receiver, a quantum decoder reconstructs the classical information, followed by polar decoding to retrieve the original image data. Our approach achieves notable improvements in image quality, with Peak Signal-to-Noise Ratio (PSNR) up to 58.27 dB for JPEG and 64.72 dB for HEIF, and Structural Similarity Index Measure (SSIM) up to 0.9994 for JPEG and 0.9999 for HEIF, outperforming classical systems, especially under low Signal-to-Noise Ratio (SNR) conditions, demonstrating the system’s enhanced ability to maintain image quality in noisy channels. These findings highlight the promise of quantum superposition-based media transmission to set new standards in reliable, high-fidelity communication for next-generation systems.
ABSTRACT This work presents a quantum communication system enhanced with adaptive coding, aimed at improving compressed image transmission performance in noisy and error‐prone environments. The proposed system integrates Joint Photographic Experts Group (JPEG) and High Efficiency Image Format (HEIF) codecs with polar codes at varying code rates. To maintain consistent bandwidth usage, source coding rates are adapted according to the corresponding channel coding rates. After transmission through the quantum channel, the respective polar and source decoders reconstruct the image. 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.
ABSTRACT The state‐of‐the‐art study entitled “quantum communications for image transmission over error‐prone channels” proposes a quantum channel model based on the properties of quantum superposition and applies it to image transmission. The work presents practical insights and valuable findings in the field. However, although the article introduces two measurement operators, and , it provides a formal proof only for the measurement operator. The proof for the measurement operator is not included. Therefore, this study aims to supplement the original paper by providing a complete proof for the measurement operator.