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Communication Dans Un Congrès Année : 2020

Multivariate $alpha$-Stable Models in OFDM-Based IoT Networks with Interference From a Poisson Spatial Field of Interferers

Résumé

The uncoordinated nature of IoT networks makes interference management a challenging problem. Motivated by NB-IoT and SCMA protocols, we study the interference statistics of a Poisson spatial field of IoT interferers exploiting OFDM. We show for a sufficiently large number of subcarriers that the interference statistics are well-approximated by a sub-Gaussian α-stable random vector with a non-isotropic underlying Gaussian random vector. This result forms a basis to improve detection and decoding algorithms at the receiver.
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Dates et versions

hal-03018298 , version 1 (22-11-2020)

Identifiants

  • HAL Id : hal-03018298 , version 1

Citer

Malcolm Egan, Laurent Clavier. Multivariate $alpha$-Stable Models in OFDM-Based IoT Networks with Interference From a Poisson Spatial Field of Interferers. DCCN 2020 - 23rd International Conference on Distributed Computer and Communication Networks: Control, Computation, Communications, Sep 2020, Virtual Event, Russia. pp.1-9. ⟨hal-03018298⟩
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