Integrated Near Field Sensing and Communications Using Unitary Approximate Message Passing Based Matrix Factorization
<|reference_start|>Integrated Near Field Sensing and Communications Using Unitary Approximate Message Passing Based Matrix Factorization: Due to the utilization of large antenna arrays at base stations (BSs) and the operations of wireless communications in high frequency bands, mobile terminals often find themselves in the near-field of the array aperture. In this work, we address the signal processing challenges of integrated near-field localization and communication in uplink transmission of an integrated sensing and communication (ISAC) system, where the BS performs joint near-field localization and signal detection (JNFLSD). We show that JNFLSD can be formulated as a matrix factorization (MF) problem with proper structures imposed on the factor matrices. Then, leveraging the variational inference (VI) and unitary approximate message passing (UAMP), we develop a low complexity Bayesian approach to MF, called UAMP-MF, to handle a generic MF problem. We then apply the UAMP-MF algorithm to solve the JNFLSD problem, where the factor matrix structures are fully exploited. Extensive simulation results are provided to demonstrate the superior performance of the proposed method.<|reference_end|>
@article{yuan2024integrated,
    title={Integrated Near Field Sensing and Communications Using Unitary
  Approximate Message Passing Based Matrix Factorization},
    author={Zhengdao Yuan and Qinghua Guo and Yonina C. Eldar and Yonghui Li},
    journal={arXiv preprint arXiv:2406.07272},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.07272},
    primaryClass={cs.IT math.IT}
}