Iterative Detection and Decoding Schemes with LLR Refinements in Cell-Free Massive MIMO Networks
<|reference_start|>Iterative Detection and Decoding Schemes with LLR Refinements in Cell-Free Massive MIMO Networks: In this paper, we propose low-complexity local detectors and log-likelihood ratio (LLR) refinement techniques for a coded cell-free massive multiple input multiple output (CF- mMIMO) systems, where an iterative detection and decoding (IDD) scheme is applied using parallel interference cancellation (PIC) and access point (AP) selection. In particular, we propose three LLR processing schemes based on the individual processing of the LLRs of each AP, LLR censoring, and a linear combination of LLRs by assuming statistical independence. We derive new closed-form expressions for the local soft minimum mean square error (MMSE)-PIC detector and receive matched filter (RMF). We also examine the system performance as the number of iterations increases. Simulations assess the performance of the proposed techniques against existing approaches.<|reference_end|>
@article{ssettumba2024iterative,
    title={Iterative Detection and Decoding Schemes with LLR Refinements in
  Cell-Free Massive MIMO Networks},
    author={T. Ssettumba, Z. Shao, L. Landau and R. C. de Lamare},
    journal={arXiv preprint arXiv:2405.13312},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.13312},
    primaryClass={cs.IT eess.SP math.IT}
}