LLR Approximation for Fading Channels Using a Bayesian Approach

Lorenzo Ortega Espluga (1) , Marion Aubault-Roudier (2) , Charly Poulliat (3) , Marie-Laure Boucheret (3) , Hanaa Al-Bitar (4) , Pau Closas (5)

1 TéSA - Télécommunications Spatiales et Aéronautiques - Telecommunications for Space ant Aeronautics
2 CNES - Centre National d'Études Spatiales [Toulouse]
3 IRIT-SC - Signal et Communications
4 TAS - Thales Alenia Space [Toulouse]
5 Northeastern University [Boston]

This letter investigates on the derivation of good log likelihood ratio (LLR) approximations under uncorrelated fading channels with partial statistical channel state information (CSI) at the receiver. While previous works focused mainly on solutions exploiting full statistical CSI over the normalized Rayleigh fading channel, in this letter, a Bayesian approach based on conjugate prior analysis is proposed to derive LLR values that only uses moments of order one and two associated with the random fading coefficients. The proposed approach is shown to be a more robust method compared to the best existing approximations, since it can be performed independently of the fading channel distribution and, in most cases, at a lower complexity. Results are validated for both binary and M -ary modulations over different uncorrelated fading channels.

Mots clés: LLR values; fading channel; channel uncertainty; M-ary modulations; best linear approximation

Domaines: Traitement du signal et de l'image [eess.SP]

Lorenzo Ortega Espluga, Marion Aubault-Roudier, Charly Poulliat, Marie-Laure Boucheret, Hanaa Al-Bitar, et al.. LLR Approximation for Fading Channels Using a Bayesian Approach. IEEE Communications Letters, 2020, 24 (6), pp.1244-1248. ⟨10.1109/LCOMM.2020.2978832⟩. ⟨hal-03246009⟩