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.
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.
As quantum communication emerges as a key technology for the future, it offers promising solutions to the limitations of classical communication systems. However, quantum communication also vulnerable to various forms of channel noise, which can introduce errors during transmission. Quantum error correction methods are critical to mitigating these errors, thereby preserving the integrity and reliability of quantum communication systems. In this study, we explore the effectiveness of the three-qubit stabilizer code for transmitting images over noisy quantum channels. We conduct a comparative analysis between the three-qubit stabilizer code and 1/3 rate polar codes, assessing their performance across uncompressed images, as well as Joint Photographic Experts Group (JPEG) and High-Efficiency Image Format (HEIF) images. Our findings indicate that the three-qubit stabilizer code offers significant advantages in quantum communication, achieving the Peak Signal-to-Noise Ratio (PSNR) up to infinity and the Structural Similarity Index Measure (SSIM) up to 1 for uncompressed images. For JPEG images, it achieves the PSNR up to 58.27 dB and the SSIM up to 0.9994, while for HEIF images, the PSNR reaches up to 64.72 dB and the SSIM up to 0.9999. These results highlight the three-qubit stabilizer code as a highly effective approach for enhancing the robustness of quantum communication systems.
Reliable transmission of high-quality video over wireless channels is challenged by fading and noise, which degrade visual quality and disrupt temporal continuity. To address these issues, this paper proposes a quantum communication framework that integrates quantum superposition with multi-input multi-output (MIMO) spatial diversity techniques to enhance robustness and efficiency in dynamic video transmission. The proposed method converts compressed videos into classical bitstreams, which are then channel-encoded and quantum-encoded into qubit superposition states. These states are transmitted over a 2×2 MIMO system employing varied diversity schemes to mitigate the effects of multipath fading and noise. At the receiver, a quantum decoder reconstructs the classical information, followed by channel decoding to retrieve the video data, and the source decoder reconstructs the final video. Simulation results demonstrate that the quantum MIMO system significantly outperforms equivalent-bandwidth classical MIMO frameworks across diverse signal-to-noise ratio (SNR) conditions, achieving a peak signal-to-noise ratio (PSNR) up to 39.12 dB, structural similarity index (SSIM) up to 0.9471, and video multi-method assessment fusion (VMAF) up to 92.47, with improved error resilience across various group of picture (GOP) formats, highlighting the potential of quantum MIMO communication for enhancing the reliability and quality of video delivery in next-generation wireless networks.
Reliable video transmission over error-prone channels remains a significant challenge due to the inherent trade-off between compression efficiency and noise resilience in conventional systems. To address these issues, this paper introduces a novel quantum Fourier transform (QFT)-based framework that integrates video compression and transmission within a unified quantum frequency-domain representation. The framework converts video data into a classical bitstream and maps it onto multi-qubit quantum states with variable encoding sizes (n), enabling flexible control over compression levels. Through the application of the QFT, these states are transformed into the frequency domain, where only selected coefficients are transmitted to reduce bandwidth requirements. At the receiver, the transmitted components are used to reconstruct the full representation, followed by inverse transformation and decoding to recover the video sequence. The performance of the proposed framework is evaluated using peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and video multi-method assessment fusion (VMAF). The results demonstrate that increasing the number of qubits enables exponential compression, achieving ratios up to 2n:1, while maintaining high reconstruction quality under ideal transmission conditions. However, higher-qubit configurations exhibit increased sensitivity to channel noise, leading to a more rapid degradation as the signal-to-noise ratio decreases. In contrast, lower-qubit configurations provide improved robustness, maintaining more stable reconstruction quality under noisy conditions, albeit with reduced compression efficiency. Among the evaluated configurations, the two-qubit system achieves an effective trade-off, providing a compression ratio of 4:1 while maintaining strong visual and structural fidelity along with enhanced resilience to channel impairments.
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 presents new opportunities for overcoming the limitations of classical wireless systems, particularly those associated with noise, fading, and interference. Building upon the principles of classical orthogonal frequency division multi-plexing (OFDM), this work proposes a quantum OFDM architecture tailored for video transmission. In the proposed system, video sequences are first compressed using the versatile video coding (VVC) standard with different group of pictures (GOP) sizes. Each GOP size is processed through a channel encoder and mapped to multi-qubit states with various qubit configurations. The quantum-encoded data is converted from serial-to-parallel form and passed through the quantum Fourier transform (QFT) to generate mutually orthogonal quantum subcarriers. Following reserialization, a cyclic prefix is appended to mitigate inter-symbol interference within the quantum channel. At the receiver, the cyclic prefix is removed, and the signal is restored to parallel before the inverse QFT (IQFT) recovers the original quantum subcarriers. Quantum decoding, classical channel decoding, and VVC reconstruction are then employed to recover the videos. Experimental evaluations across different GOP sizes and channel conditions demonstrate that quantum OFDM provides superior resilience to channel noise and improved perceptual quality compared to classical OFDM, achieving peak signal-to-noise ratio (PSNR) up to 47.60 dB, structural similarity index measure (SSIM) up to 0.9987, and video multi-method assessment fusion (VMAF) up to 96.40. Notably, the eight-qubit encoding scheme consistently achieves the highest SNR gains across all channels, underscoring the potential of quantum OFDM as a foundation for future high-quality video transmission.
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.