Abstract:
Industrial Internet of Things networks require large-volume data delivery across interdependent mission-critical components. This imposes stringent ultrareliable low-late...Show MoreMetadata
Abstract:
Industrial Internet of Things networks require large-volume data delivery across interdependent mission-critical components. This imposes stringent ultrareliable low-latency communication requirements. In this regard, cell-free network architecture has risen as a compelling solution to shorten distances between devices and access points (APs). In cell-free networks, APs simultaneously serve devices with shared time–frequency resources, utilizing channel state information acquired via pilot signals from devices. However, a limited number of orthogonal pilot sequences entails the pilot reuse across multiple links. This results in the interference among pilot signals, which, in turn, degrades the overall link utilities. A skillful pilot assignment (PA) mitigates such interference, while the combinatorial nature of handling pilot-sharing groups limits the development of an efficient protocol. This work develops a survey propagation-inspired distributed PA framework, originating from statistical physics to address the equilibrium among particle interactions, which successfully interprets the consensus among pilot-sharing groups in the PA task. This facilitates distributed and efficient addressing of complex solution spaces, leading to computation-efficient solutions.
Published in: IEEE Internet of Things Journal ( Volume: 11, Issue: 22, 15 November 2024)