Coverage and Rate Analysis for Distributed RISs-Assisted mmWave Communications
<|reference_start|>Coverage and Rate Analysis for Distributed RISs-Assisted mmWave Communications: The millimeter wave (mmWave) has received considerable interest due to its expansive bandwidth and high frequency. However, a noteworthy challenge arises from its vulnerability to blockages, leading to reduced coverage and achievable rates. To address these limitations, a potential solution is to deploy distributed reconfigurable intelligent surfaces (RISs), which comprise many low-cost and passively reflected elements, and can facilitate the establishment of extra communication links. In this paper, we leverage stochastic geometry to investigate the ergodic coverage probability and the achievable rate in both distributed RISs-assisted single-cell and multi-cell mmWave wireless communication systems. Specifically, we first establish the system model considering the stochastically distributed blockages, RISs and users by the Poisson point process. Then we give the association criterion and derive the association probabilities, the distance distributions, and the conditional coverage probabilities for two cases of associations between base stations and users without or with RISs. Finally, we use Campbell's theorem and the total probability theorem to obtain the closed-form expressions of the ergodic coverage probability and the achievable rate. Simulation results verify the effectiveness of our analysis method, and demonstrate that by deploying distributed RISs, the ergodic coverage probability is significantly improved by approximately 50%, and the achievable rate is increased by more than 1.5 times.<|reference_end|>
@article{xu2024coverage,
    title={Coverage and Rate Analysis for Distributed RISs-Assisted mmWave
  Communications},
    author={Yuan Xu, Chongwen Huang, Wei Li, Yongxu Zhu, Zhaohui Yang, Jiguang He,
  Jun Yang, Zhaoyang Zhang, Chau Yuen, Merouane Debbah},
    journal={arXiv preprint arXiv:2402.06154},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.06154},
    primaryClass={cs.IT eess.SP math.IT}
}