Multiple-input multiple-output (MIMO) communication has significantly enhanced classical telecommunication systems by utilizing multiple transmission paths to improve data rate and reliability. Recent studies suggest that MIMO architectures could similarly benefit quantum communications in lossy environments. In this work, we examine MIMO quantum communication in correlated pure-loss channels, where we model losses as probabilistic erasures. Using symmetric quantum cloning in a 2 × 2 MIMO setup, we derive average fidelity expressions to evaluate the performance under varying correlation strength of losses. Our results indicate that MIMO setups provide fidelity benefits in low-correlation scenarios, but these advantages diminish as correlation increases.
Multiple-input multiple-output (MIMO) communication has significantly enhanced classical telecommunication systems by utilizing multiple transmission paths to improve data rate and reliability. Recent studies suggest that MIMO architectures could similarly benefit quantum communications in lossy environments. In this work, we examine MIMO quantum communication in correlated pure-loss channels, where we model losses as probabilistic erasures. Using symmetric quantum cloning in a 2 × 2 MIMO setup, we derive average fidelity expressions to evaluate the performance under varying correlation strength of losses. Our results indicate that MIMO setups provide fidelity benefits in low-correlation scenarios, but these advantages diminish as correlation increases.
Characterization and exploitation of multiple channels between the transmitter and the receiver in multiple-input multiple-output (MIMO) communications brought a paradigm shift in classical communication systems. The techniques developed around MIMO communication systems not only brought unprecedented advancements in communication rates but also substantially improved the reliability of communication, measured by low error rates. We develop a framework for MIMO quantum communications with discrete-variable quantum systems. We propose a general model of MIMO quantum channels incorporating noise, losses, and crosstalk among multiple channels. We leverage the approximate quantum cloning to transmit imperfect clones of the input state over this channel setup. We demonstrate that transmitting multiple imperfect clones achieves better communication fidelity as compared to transmitting a single perfect copy of the state due to the diversity of the MIMO setup. We also demonstrate a practical tradeoff between fidelity and rate of communication and call it quantum diversity multiplexing tradeoff (DMT) due to its similarity with the well-known DMT in classical MIMO setups.
As quantum networks evolve toward a full quantum Internet, reliable transmission in quantum multiple-input multiple-output (QuMIMO) settings becomes essential, yet remains difficult due to noise, crosstalk, and the mixing of quantum information across subchannels. To improve reliability in such settings, we study an adaptive diversity strategy for discrete-variable QuMIMO systems based on universal asymmetric cloning at the transmitter and probabilistic purification at the receiver. An input qubit is encoded into M approximate clones, transmitted over an N x N multi-mode quantum channel, and recovered through a purification map optimized using available channel state information (CSI). For the given cloning asymmetry parameters, we derive an eigenvalue-based expression for the decoder-optimal end-to-end fidelity in the form of a generalized Rayleigh quotient, which enables efficient tuning of the cloner without iterative optimization. As a design choice, we employ semidefinite program (SDP) to construct the purification map for only a targeted success probability p. This numerical framework is used to study fixed-noise, dimension-scaling noise, and stochastic depolarization regimes. A cloning asymmetry index is introduced to quantify the distribution of quantum information across the multiple subchannels across these operating conditions. The results show that the proposed scheme yields significant fidelity gains in crosstalk-dominated settings and automatically adapts to channel symmetry and channel conditions. This work provides design guidelines for future QuMIMO systems and establishes a robust baseline for more advanced transmission and decoding strategies.
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.
As quantum networks evolve toward a full quantum Internet, reliable transmission in quantum multiple-input multiple-output (QuMIMO) settings becomes essential, yet remains difficult due to noise, crosstalk, and the mixing of quantum information across subchannels. To improve reliability in such settings, we study an adaptive diversity strategy for discrete-variable QuMIMO systems based on universal asymmetric cloning at the transmitter and probabilistic purification at the receiver. An input qubit is encoded into M approximate clones, transmitted over an N × N multi-mode quantum channel, and recovered through a purification map optimized using available channel state information (CSI). For the given cloning asymmetry parameters, we derive an eigenvalue-based expression for the decoder-optimal end-to-end fidelity in the form of a generalized Rayleigh quotient, which enables efficient tuning of the cloner without iterative optimization. As a design choice, we employ semidefinite program (SDP) to construct the purification map for only a targeted success probability p . This numerical framework is used to study fixed-noise, dimension-scaling noise, and stochastic depolarization regimes. A cloning asymmetry index is introduced to quantify the distribution of quantum information across the multiple subchannels across these operating conditions. The results show that the proposed scheme yields significant fidelity gains in crosstalk-dominated settings and automatically adapts to channel symmetry and channel conditions. This work provides design guidelines for future QuMIMO systems and establishes a robust baseline for more advanced transmission and decoding strategies.
Abstract The paper explores the field of quantum-enhanced channel estimation of terahertz (THz) cell-free massive multiple-input multiple-output (MIMO) systems. Although quantum sensing has been suggested to be used in wireless communications, its practical benefit over classical techniques is not well known. We identify systematically the signal-to-noise ratio (SNR) regime in which quantum sensing is able to offer an advantage. The results demonstrate that THz systems operating in the low pilot SNR regime ( ∼ ∼ 3 dB) achieve 14–103.1% sum-rate improvement with quantum-enhanced estimation, compablack to only 2–5% at millimeter-wave (mmWave) frequencies where pilot SNR exceeds 13 dB. The 6–33 × × greater quantum advantage at THz frequencies stems from the fundamental difference in operating regimes: THz systems are noise-limited due to severe path loss ( ∼ ∼ 100 dB at 10 m), while mmWave systems are interference-limited with near-perfect classical estimation. Our results identify THz cell-free multiple-input multiple-output (MIMO) as a compelling application for quantum-enhanced wireless communications and provide design guidelines for practical deployment in future sixth-generation (6G) networks.
Multiple-input multiple-output (MIMO) technology utilizes multiple antennas at the transmitter and receiver to enhance data transmission speeds and reliability. Traditional MIMO decoding methods, however, can become increasingly complex as the number of antennas and modulation order rises. Quantum computing brings forth a new realm of information processing with significant potential. This study investigates the applicability of quantum algorithms for decoding information in MIMO wireless communication systems. Specifically, the Dürr-Høyer quantum search, based on Grover’s algorithm, and optimal quantum sorting algorithms are leveraged to reduce the query complexity with an analysis of the complexity and achievable bit error rate performance of the quantum-assisted decoders. The study considers cases of MIMO diversity, spatial modulation, and multiplexing transmission using both maximum-likelihood and fixed-complexity sphere decoders. By examining a variety of communication scenarios, this work aims to assess the applicability of quantum algorithms across different operational regimes and aids in extending the methodology to other communication systems.