Fundamental Limits of Optical Fiber MIMO Channels With Finite Blocklength
<|reference_start|>Fundamental Limits of Optical Fiber MIMO Channels With Finite Blocklength: The multiple-input and multiple-output (MIMO) technique is regarded as a promising approach to boost the throughput and reliability of optical fiber communications. However, the fundamental limits of optical fiber MIMO systems with finite block-length (FBL) are not available in the literature. This paper studies the fundamental limits of optical fiber multicore/multimode systems in the FBL regime when the coding rate is a perturbation within $\mathcal{O}(\frac{1}{\sqrt{ML}})$ of the capacity, where M and L represent the number of transmit channels and blocklength, respectively. Considering the Jacobi MIMO channel, which was proposed to model the nearly lossless propagation and the crosstalks in optical fiber systems, we derive the upper and lower bounds for the optimal error probability. For that purpose, we first set up the central limit theorem for the information density in the asymptotic regime where the number of transmit, receive, available channels and the blocklength go to infinity at the same pace. The result is then utilized to derive the upper and lower bounds for the optimal average error probability with the concerned rate. The derived theoretical results reveal interesting physical insights for Jacobi MIMO channels with FBL. First, the derived bounds for Jacobi channels degenerate to those for Rayleigh channels when the number of available channels approaches infinity. Second, the high signal-to-noise (SNR) approximation indicates that a larger number of available channels results in a larger error probability. Numerical results validate the accuracy of the theoretical results and show that the derived bounds are closer to the performance of practical LDPC codes than outage probability.<|reference_end|>
@article{zhang2024fundamental,
    title={Fundamental Limits of Optical Fiber MIMO Channels With Finite
  Blocklength},
    author={Xin Zhang, Dongfang Xu, Shenghui Song, M'erouane Debbah},
    journal={arXiv preprint arXiv:2404.04477},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.04477},
    primaryClass={cs.IT math.IT}
}