# Transmit and Receive Diversity in MIMO Quantum Communication for High-Fidelity Video Transmission
## 4 Results and Discussion
While the quantum system continues to outperform its classical counterpart, and MISO and SIMO configurations show better results than SISO, the overall video quality is reduced compared to that achieved with a GOP size of 16. The reason is that, as the GOP size increases, more frames are encoded using inter-frame prediction. Since these frames depend on preceding intra and inter-coded frames within the same GOP, any error introduced partway through can propagate and severely impact the quality of the remaining predicted frames. This trend is evident in Figures 3-5, where performance metrics progressively decrease as the GOP size grows from 8 to 16 and further to 32. Therefore, to maintain consistent video quality in these scenarios, it is essential to adopt adaptive error-correction techniques that dynamically allocate protection based on the GOP frame hierarchy. Coupling these methods with error-resilient video-encoding approaches, such as flexible macroblock ordering or intra-refresh strategies, can help localize errors and prevent widespread quality degradation. These combined solutions offer a promising direction to improve robustness in video transmission over quantum and classical channels alike. Furthermore, transmit (MISO) and receive (SIMO) diversity schemes enhance system robustness by mitigating the adverse effects of signal degradation in both classical and quantum communication systems. In classical systems, diversity techniques primarily address channel fading caused by multipath propagation and interference. These methods help improve signal quality and reliability by combining multiple signal paths at the receiver. In quantum systems, however, the communication channel is also affected by unique impairments such as quantum noise, decoherence, and quantum fading, phenomena that  
Figure 3: Comparison of average PSNR (**left column**), SSIM (**center column**), and VMAF (**right column**) for classical (C) and quantum (Q) systems across diversity schemes: (**a–c**) \(1\times 1\) SISO, (**d–f**) \(2\times 1\) MISO, and (**g–i**) \(1\times 2\) SIMO with GOP size 8.  
do not exist in classical transmission. While classical fading impacts the amplitude and phase of transmitted signals, quantum fading and noise can disrupt the delicate superposition states essential for quantum communication. Despite these challenges, diversity schemes such as MISO and SIMO still contribute to performance improvements in quantum systems by increasing redundancy and reception reliability. Moreover, the use of quantum superposition further enhances the system's ability to resist quantum impairments. By representing multiple bit states simultaneously, quantum encoding allows information to be distributed across parallel quantum states, making the system inherently more tolerant to noise and fading. As a result, quantum-enhanced systems demonstrate superior resilience and reconstruction accuracy, especially in low-SNR scenarios, as confirmed by PSNR, SSIM, and VMAF metrics across different diversity schemes and GOP sizes. In addition, the impact of varying frame rates and resolutions on the performance of the proposed quantum MIMO communication system is evaluated, with GOP size 8 selected as a representative test case, as summarized in Table 2. The comparative analysis demonstrates that variations in resolution and frame rate have minimal effect on the maximum channel SNR gains achieved by the quantum system compared to the classical baseline. This channel SNR gain is quantified using Equation (35). \[\Delta\text{SNR}(Q)=\text{SNR}_{\text{classical}}(Q)-\text{SNR}_{\text{ quantum}}(Q) \tag{35}\]  
where \(\text{SNR}_{\text{classical}}(Q)\) and \(\text{SNR}_{\text{quantum}}(Q)\) denote the channel SNR values required by the baseline and proposed systems, respectively, to achieve the same quality level \(Q\). The consistency of the results indicates that both quantum and classical communication systems respond similarly to changes in these video parameters.