Eavesdropping and Jamming via Pilot Attacks in 5G Massive MIMO

  1. Marc Bernice Angoue Avele 1
  2. Darian Pérez Adán
  3. Dariel Pereira Ruisánchez 2
  1. 1 Universidade de Vigo
    info

    Universidade de Vigo

    Vigo, España

    ROR https://ror.org/05rdf8595

  2. 2 Universidade da Coruña
    info

    Universidade da Coruña

    La Coruña, España

    ROR https://ror.org/01qckj285

Libro:
VI Congreso XoveTIC: impulsando el talento científico
  1. Manuel Lagos Rodríguez (ed. lit.)
  2. Álvaro Leitao Rodríguez (ed. lit.)
  3. Tirso Varela Rodeiro (ed. lit.)
  4. Javier Pereira Loureiro (coord.)
  5. Manuel Francisco González Penedo (coord.)

Editorial: Servizo de Publicacións ; Universidade da Coruña

Año de publicación: 2023

Congreso: XoveTIC (6. 2023. A Coruña)

Tipo: Aportación congreso

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Resumen

In thiswork, we investigate pilot attacks for 5G single-cell multi-user massive multipleinput multiple-output (MaMIMO) systems with a single-antenna active eavesdropper and a single-antenna jammer operating in time-division duplex (TDD) schemes. Firstly, we describe the attacks when the base station (BS) estimates the channel state information (CSI) based on the uplink pilot transmissions. Finally, we propose a reinforcement learning (RL)-based framework for maximizing the system sum rate that proved robust to the eavesdropping and jamming attacks

Fuente de los datos: Dialnet