Coded random access for massive MTC under statistical channel knowledge

Diane Duchemin 1 Lélio Chetot 1 Jean-Marie Gorce 1 Claire Goursaud 1
1 MARACAS - Modèle et algorithmes pour des systèmes de communication fiables
Inria Grenoble - Rhône-Alpes, CITI - CITI Centre of Innovation in Telecommunications and Integration of services
Abstract : This paper focuses on random uplink transmissions of a subset of nodes disseminated in a cell. Under the constraints of massive Machine Type Communication (mMTC) in cellular Low Power Wide Area Networks (LPWAN) and Ultra Reliable Low Latency Communications (URLLC), improving the capability of a receiver to detect simultaneously several transmissions with a high probability is important. Considering a very limited coordination between the receiver and the distributed transmitters, the usage of coded Non Orthogonal Multiple Access (NOMA) strategies is seducing. In this framework, we target synchronous direct data transmissions and propose an optimal detector of the active users with channel state information at the receiver limited to statistical knowledge. This algorithm is based on a Maximum Likelihood (ML) detector, under statistical channel knowledge only. We give the formulation of the optimal detector and we evaluate its performance, with different codelengths, code types (random Gaussian and Grassmannian codes) and for various number of antennas at the base station.
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Diane Duchemin, Lélio Chetot, Jean-Marie Gorce, Claire Goursaud. Coded random access for massive MTC under statistical channel knowledge. SPAWC 2019 - 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, Jul 2019, Cannes, France. pp.1-5, ⟨10.1109/SPAWC.2019.8815491⟩. ⟨hal-02153735⟩

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