Channel Modeling Using Rayleigh and Rice Sum Approximation


Abstract:

In this paper we develop an identification technique for the multipath wireless channel utilizing a discrete sum distribution approximation. We focus on three of the main distributions for the multi-path channel: Rayleigh, Rice and Nakagami-m. The distributions are approximated using a weighted sum of a Rayleigh and up to three distributions. The estimation procedure is based on the Maximum Likelihood approach and Akaike's Information Criterion. We show via simulations that when the channel is Rayleigh distributed, the estimation yields the correct Rayleigh distribution. When the channel distribution is Rice, the estimation yields one Rician term, whilst when the true channel distribution is Nakagami- m, the estimation yields an adequate approximation with a Rayleigh and Rice terms.

Año de publicación:

2024

Keywords:

  • Channel modeling
  • Expectation-maximization
  • Maximum likelihood
  • sum distribution approximation

Fuente:

scopusscopus

Tipo de documento:

Other

Estado:

Acceso restringido

Áreas de conocimiento:

  • Comunicación
  • Proceso estocástico
  • Telecomunicaciones

Áreas temáticas de Dewey:

  • Física aplicada
  • Probabilidades y matemática aplicada
  • Sistemas
Procesado con IAProcesado con IA

Objetivos de Desarrollo Sostenible:

  • ODS 12: Producción y consumo responsables
  • ODS 15: Vida de ecosistemas terrestres
  • ODS 17: Alianzas para lograr los objetivos
Procesado con IAProcesado con IA