ISSPIT 2016, 16th International Symposium on Signal Processing and Information Technology, 12-14 December 2016, Limassol, Cyprus
This paper presents an iterative Variational Bayes (VB) algorithm that allows sparse recovery of the desired transmitted vector. The VB algorithm is derived based on the latent variables introduced in the Bayesian model in hand. The proposed algorithm is applied to he Angle-of-Arrival (AoA) estimation problem and simulations demonstrate the potential of the proposed VB algorithm when compared to existing sparse recovery
and compressed sensing algorithms, especially in the case of closely spaced sources. Furthermore, the proposed algorithm does not require prior knowledge of the number
of sources and operates with only one snapshot.
Type:
Conférence
City:
Limassol
Date:
2016-12-12
Department:
Systèmes de Communication
Eurecom Ref:
5127
Copyright:
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