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- W3207833465 abstract "In this paper, the backhauling topology of an integrated and backhaul (IAB) network is designed to sustain bursty traffic with the highest probability. To ensure sequential DU-MT or MT-DU transmissions, the topology is characterized by a directed acyclic graph (DAG). First, the Bayes' theorem is used to transform the probability of sustaining the UE traffic into the probability of generating a DAG, and then the transformed problem is decomposed into two subproblems: 1) The link traffic load is determined under the condition that a DAG is formed; 2) Based on the link traffic load, the links that are critical for sustaining the UE traffic are identified, and then a new DAG is generated by maximizing the joint probability of links in the new DAG. Given random initial DAG, the two subproblems are iteratively solved until obtaining a final DAG. Theoretical analysis validates that the above iterative procedures converge to a single DAG, and simulations confirm that the convergence can be achieved within tens of iterations. Simulation results also show that the backhauling approach developed in this paper can support 56.41% higher traffic variations and achieve a 29.32% lower average hop-count than the existing topology generation schemes." @default.
- W3207833465 created "2021-10-25" @default.
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- W3207833465 date "2023-04-01" @default.
- W3207833465 modified "2023-09-28" @default.
- W3207833465 title "A Bayesian Approach to the Design of Backhauling Topology for 5G IAB Networks" @default.
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- W3207833465 doi "https://doi.org/10.1109/tmc.2021.3118958" @default.
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